{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据可视化\n",
    "\n",
    "Pandas 的数据可视化使用 matplotlib 为基础组件。更基础的信息可参阅 matplotlib 相关内容。本节主要介绍 Pandas 里提供的比 matplotlib 更便捷的数据可视化操作。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 线型图\n",
    "\n",
    "Series 和 DataFrame 都提供了一个 `plot` 的函数。可以直接画出线形图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1000.000000\n",
       "mean       15.391024\n",
       "std         5.685882\n",
       "min        -2.955805\n",
       "25%        12.240776\n",
       "50%        15.866531\n",
       "75%        19.368695\n",
       "max        29.181894\n",
       "dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))\n",
    "ts = ts.cumsum()\n",
    "ts.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HZO3++xcej3dvXqb4GUQG8BEy6RQE4Uh350jgb+2Smp8sMIjBBwCLJX3Wd22VDbUuG/Yc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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9bd8331c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/foEZmmOhVStZkejTR5ZtV62yz02bFhhPomQMuiqRTjp0EAFQWQkUFUnbggUS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\nJQQVDIqihKCCQVGUEP4fxFpUilEx0jgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x868d7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ts.plot? for more help\n",
    "ts.plot(title='cumsum', style='r-', ylim=[-30, 30], figsize=(4, 3));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-3.295144</td>\n",
       "      <td>22.795661</td>\n",
       "      <td>-5.886238</td>\n",
       "      <td>-37.999975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.628413</td>\n",
       "      <td>19.796374</td>\n",
       "      <td>8.198246</td>\n",
       "      <td>21.634415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-26.348041</td>\n",
       "      <td>-13.736122</td>\n",
       "      <td>-22.131242</td>\n",
       "      <td>-74.229050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-7.867078</td>\n",
       "      <td>3.510378</td>\n",
       "      <td>-12.802391</td>\n",
       "      <td>-64.330701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-4.039818</td>\n",
       "      <td>27.847130</td>\n",
       "      <td>-7.362244</td>\n",
       "      <td>-32.643535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.951503</td>\n",
       "      <td>40.762342</td>\n",
       "      <td>0.811932</td>\n",
       "      <td>-24.012049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.474729</td>\n",
       "      <td>58.372643</td>\n",
       "      <td>12.726630</td>\n",
       "      <td>6.441942</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 A            B            C            D\n",
       "count  1000.000000  1000.000000  1000.000000  1000.000000\n",
       "mean     -3.295144    22.795661    -5.886238   -37.999975\n",
       "std       7.628413    19.796374     8.198246    21.634415\n",
       "min     -26.348041   -13.736122   -22.131242   -74.229050\n",
       "25%      -7.867078     3.510378   -12.802391   -64.330701\n",
       "50%      -4.039818    27.847130    -7.362244   -32.643535\n",
       "75%       0.951503    40.762342     0.811932   -24.012049\n",
       "max      17.474729    58.372643    12.726630     6.441942"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=list('ABCD'))\n",
    "df = df.cumsum()\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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luWNu9pYkZxcyf5QPnZo3qfJakiThYmdJGzdbwpKV8M4pPxwlKi0PSzMTxnVp\nVqfzr5LcVCF47/4OesxS9u9aCCd+hPkXwbEeIlp2vqmsew2AsR+JcMkdr4OpJWgMnOAX10NxHmx5\nUcTPx5+D1FDo/YTSjtDUDOYchJ+HiEiciMPCJwBgZiVMOyHbwNwG7G/y71hFpQ44HHuYZ/c+a7Sv\nWFuMh40Hi4cuZuHRhYRnhnM59TITNk4wGjer0yyOxh1llNcoBnkOQkLC6xGvat33ttTwv993lWdW\nnCkXL//hliCszE0Y7ONW7pzfHu7NoHauzBlSs25JW58bzGvjlTh9fVJXVn4DxOrrTR6b5xlr+lHH\nxDI9on7umx4h7O4z1sJ9v4GJqXiwjHwbZm0EEwP7/aanhLAHUeUyNVSslw2t9NA5y498BRvmKPvb\njQL3TmK9zTDxcGhk5BXnkZR3Q7UCVe4Qll9aXrrewVmRH11du+Lv7s+yccvKndO/WX8+GPgBD3V8\niN/G/saMjjPwauJFyybVV+JuaYF/MjyNl9adQ1PGfPLZjitsuRDPou3BFJWIcEtZlgmKz+K+ni3w\na1neZNO1hQN/PdEXa4ua9UG1Mjflnu6eTPZvTqdmyptBYkNE7yRfUdZ3vilMICWFwi4OsOrBiiNf\nakt2gmjg7TtWOF31DH4BvAfC/PPw6Hbjc5y8ocigllFZx6uJwd8hK0ZZH7JAeRPwGV0n069rnt/3\nPCPXjaRYqxbbUylPZmEmJxNOMtdvLhcevsC6SetKjz3bQ2j9zlbOLB+3nFmdlDf1JWOWMLndZKzN\nrG/43o1PPaoB034WmuvuoET2vzQcB2tzI9v58mORtHO3Y1Z/b5KyC8kqKMHHvXztnNri0cSKr6d3\nJzO/GL93RRRJXGZ+nd+nSi5tABcfKM4XIZHHvjM+XpQNKaHg3qHi82+E3FTRS7b1kMrHNGkufloN\ngsjDMP+CcPBueUEcn/YHdJh0/fu0nwBTfgKrJuJhkXgR2t24wE/ILGDJwTAeHehNS2ebG75OWWRZ\n5nj8cQBOJZzC3cadNg5tbkr9pV2RuzA3MWdYy2H1fi+VG+d4/HG0spaBzQeW7vt48Mc4WzrTxqFN\n6b4eHj3o4dGD1g6taWJRtZm5OtyyAt9QsKfnFbPjYgLTerfk0+3GdVj0tXBCEoU26eNhV29zcrA2\nx9XOgpScImIzGkDDTwqCLlPB2hEOfV7xmLRrdSvw9bXovfpVPfahdZAdD45exrVvOkwEkwpeNsd+\nJPwAAF3uFcIe4O5voffjtfJH9Pt4DwC/HQln8f1+3NezbkI7I7IiStef3PWkuMfY3+jdtHedXL8i\nsoqyWB28mm/PfgvA+dnn1QJHMzfIAAAgAElEQVR/jZidETtxsHSgi6uS4zOxzcRKx9/ve3+d3fuW\nMenIskzq0qVk790HwDv/iqiT3t5OACRlF1Ci0fLzwTCj87ZdTOCLnVfYeDYWEwnae1Sh4adchT8m\nQ/ihqicVsgOO/2S069SboxnfpSlxGTdBw9dnnWq1Iv69IEPErXesQFu+S9cCMPVq3c4h/pxYdpxc\n9VgLGyWu3qsfPPwvzNxgbL4xpP8zyPpCrM0NIqlsnKHtiBuectl2mQvWnePH/df435rAWkdXbQjd\ngFSmeOzW8K21umZV/Hbht1JhDxCaEVqv91OpGSHpIaVJVIWaQg7GHGS893jMTG6+vn3LCPyisDCS\nFn9O3KuvAvDHsUgAWjrbYG9lRkpOEUHxQov/ero/e18cyqB2rsRm5PPN3qtsOBPLJL/muNiVj9Ax\nImQbhO2Hg4uqntTKabD9FSFwr2yHjGgAmjtaE5eRX/99eNfOhncd4T0n+FKnMbt3EsKx/V267c7w\n+C4RBWPjCqnX6u7++RmgLYbR79+Y87T1EGh3/Qray1xeIEl2JM+2BV/vDr2hB+nzq8/y3KqzpdvR\naeWv8en2YDaejeVEeO16HlzNuGrkhANYH7KewCSRT6DRajgad5SZW2fy87mfa3z9gIQAJm6cyA+B\nP5Ru/3rxVwD+HP9n6T6VyinRlnA++Xy932fztc08tOUhpm6eyoh1IyjSFBGUGkSBpoD+zfvX+/0r\nolEL/PjMfPYEiUJmRVFRAGizsozGDPZxRZZh2dEIJn0nYrb9WzrSxs2OX2b3wsUgeapP62rEr+o1\n4PCDELyl8nGGwjzxoqgF84fQcps7WpNXpCEzv56ddkGby+9rrothv38ZPHkAnj4KLfsIR6erDyTU\nQXln/ZvF3vfFdj2Eel6IyeTLXSG8G9uTPoU/MOG7Y3y5O4QBn+wtdcRXl38C49h8Lo5Bn+5l56WE\n0npKFTnvf9hf/TegwKRAJm+aTN8VfUnJT+Hfa/9yOPYwHjYebJmyBU87z1JTTnS2UAZ+v/Q7c3bN\n4VzyOb4L/O56lzciOjuaoWuGMn/ffCKzIvkr6C9kWebn88pDw8/NDztzOyKzIqt93TuRH8/9yENb\nH+JyaiWJgHXEd2e/43yK8mDZEbGDqxni+9XeuX293rsyGrUN/6WP13FYdmbRfX50/OnX0snmFgpB\n+tSwttzj78nJ8HRWnRQPhFEd3fHSOeGsLUz5fJofj/wuNJ5WzrZV39QwQWn1DHg1WrEdG5KtNEbh\niC79OU1oz56OotVebEY+jjbls3XrBE0xIIGFnbCJJ10S29bCxIWZpSL89fiMgT3vCvPP9coR7HgD\n4s6Cqy+M/1RcS49WK94oBjwHAUvFPueahbJWh9m/nSA9T3lghhuUsk7MKqiWozUoPgtzU0WniUnP\n5+kVZ7C1NMNEgjVPCr/DsWupxGbkczg0hb3BSRSWaLA0K29myijI4I/Lf/CU31NEZ0fz2I7HSiNx\n7v/3fjq7iLesQZ6D8Grixfap20krSGPomqFkFQlF5b9r/xld82T8Sfo061PlZ/k+8HvSCpS3j+yi\nbP4K+ouAhACcrZxZ0GsBkiTRqkkrDsUc4k/7P5nZcaZqy6+AK2kimi02J5ZOLp3q9Np5xXlkFWXR\n1LYphRrjIozhmeEk5ydjb25PM9uGyR9ptBp+3pkzvLHpYyaHHeabZbsxO3e69Njpi0K4t3MTJRBe\nNYiDX/pwb6MvuYO1EgPe0rmKcKaiXGGTHmCQEBFfSUVMfWw7wMW/xdLMGmSZ5o7iPrHp9WjHP/4D\nIMO4j4QW/9xZEf1yPdqNEssDnyqtActyfq2I7ok8Aqd/Ny5nAEqI5NFvxLLPHGjW7YY/Rll+PnCN\n/87HUVBsrMVbmStf1fjMAq4kZPNLGX+Nngsxmfy4/xrjvz7EqC8OGB0r0cpk5hejlUVIrZW5KcM7\nuDOzXyvu6d6cIo2Wi7FZ5a4pyzLvH3+fXy78wrH4Y5xJOkOxtpi/7xZ/+5T8FM4mnaV/s/480OGB\n0vMcLByQkEgvSCe7KJtrmdd42u/p0vMe3/k4mhqGynZx6YKpZMqigEVoZS3vD3yfSW2F32as91hi\ncmJYFLCoVJtUMcbSVCgwx+OOk5JfN6XO80vyORF/gsGrBzN6/Wj6rexX+oAe1mIYbR3aEpoRyon4\nEwzwHICJ1DCit9EJ/OL4eCIffZSsACHgeyYG45suXod3txNhTD+tPQKAs85c42Btzh+P9WHj0wPK\nXc9Q4Hs6XkfgB66Cj5qL+uot+sDgBWJ/dmLF4w99AS7twM5DbLcdASX5cPzHUoG/63Il59YFp5cJ\n+3zHu8W2c5uqTSseXUAyhTN/wO53yx/XlMDOt4z35Zap5xF7xnh7yIIaTbsqPt4WzLyVZ8kvVoTg\nIwO8ufzuOLbPHwxAQEQaY786yIdbg0jJKSx3jQd/OV4uWktPa1fxlvfjQz3KHevhJd6OjocZf+bt\nFxPouFCktQOkFaQRnR2NmYkZbR3aMr/HfEBEy3jYehida2piipOVEyn5KaWO1XZO7fB18i0d4/+n\nP+8fe/86vxVIyE0oXbcxt6GlvfK3NtQWH2ivPGyC0oIqrbh4J2OqCxJYG7KW4WuHo5VrZiKsiJcO\nvMQTO5+gSFsEQG6xUKi+GvYVXw7/Eh8nH/ZH7yc+N57WDq1rfb8bpdEJ/IQPPyLv2HGSNv4DQKes\nWF46swqAPe7ilVmOF+aUJtaKRWqIrxvddf+whjR1sKK5gxWvju+Amel1Pu7JJcp68+4iaQggQ2cP\n1WqUWi5FeULz9ZsOU34WGaWTdBpv9PFSv8G60zF8t7ceIia0WuEg9hktQjCri4kJjNEJlszo8sc3\nz4OcBBj7sbJvZZmQsPNrlPUhL4Ode/XvXwWV2ebnjWiHiYlEG1c7zE0lPtuhJJhF6zKbNVq5dD3H\nIMP60MvDCflgPE8Mas3uF4awb8EwIj6ZwPiu5V+p3ZtY0be1M38ei6SoRMvpyHS8X93C3L9OU4ii\nCcbmxBKdHY2nnSemJqY83FmpG3R327vLXdfH0Ye/Q//maNxRgNI4+VUTVpWOWRuyll8v/MqOiB2l\n+7SylvySfOJy4ghMCqRVk1alx/JLlLdHTzulPLSNuQ1nZ53FVDLljcNvMGLdCMIywnj10KtcTCnz\ntnaHUrYo2bA1w0rNPBtDNxpFPF0PjVZDUGoQSXlJHIk7Uu74l8O+ZLjXcMxMzBjfenzpfpMGFLuN\nSuBnpMSSs1u0tzOPEPZw2wLRXzbYyYvmfURoXgtddcUmVtcpuavDxsKMI6+OYO7Q69iZU68pzTRA\n1Fe3sBVRLRlRkB4J7znD0pFCs16ry36zawpth4uHg2NL8OoPualIksSLo4UG9+P+OoyK0ZMVK6Jj\nbsRZ2u9p8flCdkBemYgUfYhl7yeg8xRlf6EuI1arhZgAEet//3IY+sqNzb8SylYbXTq7F+vn9sdV\nF1llYWZSqqHriUrL43RkOm1f38rgRftYd8r4QdbS2QYLMxPenNiJdtVIunt8UGsSsgo4EZ7K1guK\nn8bUSlnffy2YmOwYWtgLP4iZiRm/jvmVz4Z8VmG8/QgvEUIamRVJd/fumOtKTXRx7cLWKSJk09PO\nk6/OfMWCA8ob02cBn9FnRR92ROxAI2v4YOAHAMzuNJueHj0B2DR5Ezbmxv4MMxMzIy1y8j+T2RK2\nhQe3PMhrh14j2zDD+Q4kLNPYFJhemM4D/4k3o4VHF7Lk/JKKTgOEkM8tziUxN5Fvzn7DtP+mMXLd\nSEq0JXg38Wb9pPU81/05fJ18GdVqVKnpZoTXCPo27QvAhDYTKr1+fVPvTltJksYBXwOmwFJZlj+p\nbKxVQgYJ/o40zRDb+RZWWBcJIdBj/UqmeLpw/BdHuqZcY53vCCNzTRVzuP4AfXKPHn0SkGNLoQmH\nGJQF+Pd5Zd3Gxfg8h5YQLbIsnx3pw8W4TC7Hl7cH15iSQlj5AHj2hJFvKfNpWY1kp7JIkoiFz4oV\nYaVP6PrHyrJ4uPWdC2YWIspH1sLlf0TJBq0GLqwVxcx8x0Pne2r/ucqw/GgEAJZmJszq14pRnTyu\nO97URCIwOoPnVyt+lpfW1y7cbpCPKyYSBISnoTWIxDKxVAR+cM5+AKa3n16673qO1xkdZ3Aw5iBH\n4o7gYmX8nWnZpCVT2k1h49WNRvsDkwL5K+gvAHZH7sbZyhl/d38uPHyh9H6PdH6Eto4VKzIv9HyB\np/c8XW7/f2H/EZ4ZzuqJqyud7+1MfE48KfkpdHfvzvjW44nJjmFj6Eayi7ON6tsUa4oxL9PDYdPV\nTbx37D3MTMzIL8mnT1Pjv7mfmx/tndvT3rk9/9ft/8rde+nYpfXzoWpAvWr4kiSZAt8D44FOwIOS\nJF3XLX6gqwlrBotpFTi64bNvF16//kIrT/GPIg0dQe+kK1iWFNKkmgLfCG0FZgO906zNMFH8S49L\nOxG1c21fxdcyL+MTcGghqkTqrte5uQMx6fnkFdWykFrcWQjbB4cWi/LCFzeIePumXao+tyLu0mXh\nxp4RdvucZHjXCYpyROimnmG6B2FyMPw2RonK6XB9DSUuI59Hfz9Jcrawr2fmFfPC2kBiDWLotVqZ\nWb+ewPvVLcz69QSnI9NZHRDN3X7NufLBeN6cWPHX5OEB3gCcfWs0/i0dOVLH/YVtLMxo6WxDUEI2\nvx+JAOD0W8OxdBOZucWZSuTTSK/r5xAYohfMfm5+5Y6VjdhIyU9h1jalhsr5lPOlbxN6rM2s6ejS\nsdL7DfQcyPwe8/nrrr/KHbuUWr5UtlYrM/HbQ6zWRbvpKdZo2RechCzL3PvDET7aGkR+Ud3XY9Jo\nNXViS6+KQ7EiofK9Ae/xYIcHean3S+y+Xyg9eh8NQHBaMFFZUczdPZeMAqGB/nTuJ4q1xaXmtJMJ\nJ7Ezt2PNxDX8ffffvNT7pXqff22pb5NOH+CqLMthsiwXAauBSlMy8y3gUGeJHT0kQptBwchxmP01\nHNtrn5XGvbcfIl6ZF/Z2xsrcFG1+Pkmff05RZBWxx1oNfNdHhBTqHbFajRCmqaHgMxZmbRLmCj2t\nBkJOokjGcvWFtzPg1Shhyuj3jHhAGOLYErQlpSGbPu52yDJcS6okIqa6rH5IWf/ADaKOKhE3NeRc\ndAYFjm3Fg03WiIidP+8BdNpsCwOThFMrtJIZ/POMss93nMiYvQ7f7g1l35Vk1p6KJiQxm3f+vcSG\nM7E8u1Ixm60KiOJQqBDWh0JTmPrjUbILSujf1qWyywLwUN9WXP1wPE62FthamhGSKEx+H9/btXTM\n5nnCuX+jTcjauNqWOtwtzExIKVTMRPtmLyE/ZiaFieN5b10xmfnFxKTnVXnNp/2fZtWEVUb2fj1T\nfacabX95+kvA2B/Qy6NXjT6DiWTC410fx8/Nj5c7/0J28Ps45z6KhFRh8a24zHwuxmbx6oYLRqa1\nlSeieHRZAK1f28qZqAyWHAyj48Lt7Auu22qgw9cO59m9z5KYW3+BDnsi93Ag5gDOVs5G/hAbcxsG\neQ4ySsbadHUT35z9hiOxR9gSvoWr6VcrNIUN8hxEJ5dO+Dr54mDpUG9zryvqW+B7AoZG1RjdvlIk\nSXpSkqRTkiSdinOBGO1gcmwk3njEjE5dkyE3SWS+LvaFK9sxb9oUgB5vP0XGxk1krF1L6i9LiXr0\nMeSKtHcQ5Xt/GgwpOmffJd3r85YXYckwcbxZN6UKox7DdP67vxXHrRxg+OsiHLLseCed3TQlBIBW\nLsLeHF0NgVApBZmiqUhZvAfX+FLxmflM/v4I72y+JPwNIDKK9aGX9/0OTZUQywIseKtodul27F3L\n2dfpQwpLKtfwZFlm12UhDC7FZTLmy4NsPBsLwJmoDIIThIlrTYDytTAsL93Vs+p/Gr3z3dTg1z+x\nm6Ilt29qz7mFYzi7cEzZU6tFGzel3tKJ10ZyLUP4YR7v8jjNHK15ZfD9FKUN5XJ8Fvf+cIRBn1by\nBmiArbktXVy7VGhedLdxZ92kdfyv5//wsvdi8zWRUDejwwy+HfEtz/d4nnnd59X4c8Rl5BObkU9W\ntivI5rS0GMi87vPIL8k3ihGPy8hn+OL9pdsfbQlibUA0xRotablFFV77o61BNZ5PZWQVZZFemM7B\nmIOMWj+KrWFbORhzsM6uD8KUM3//fA7GHMTfzb/c38HwzcvPzY+1IWtLHeifnPyEKZunkFWUxcu9\nXzYqevZKn7r1Y9U39S3wK9KxjOoNyLK8RJblXrIs90I2pTB5LE9kiEzImJBf2W1jTTEIwb/lRSxa\nNkMyE5fNWLOG3KMiHr44Lo6C85XYb7/2Uxplg4ghTwsTceZ63CswIbgZpMhXpziYZ08R9hi2X2w6\nCU2qOhpghcSegU90jQ0mfCGKiY39CCZ/X6PSwLIs8/2+q+y/IkL0AqMzRPXKTgYvW14DRIEyg3+E\nqLQ8NmoGAZAjWzFwgzmPrr7CzKUnjK4fnJDF6C8OEJWax88Hw0pDJY9dM46GsDI34ekVZ4jNyOdy\nXBZPDWtLxCcTmDO0bWnIbE2K2310b1deGtuecwvHYG/gwLc0M8XBxrzaPp6ytHGzLZ2vk60FiXlC\n69TbZf9vSBscbcS1r+ma36RWEB5aEzo4d+CxLo8ZOX2b2jZlWMthPNH1iVJHb3WJSMllwCd7GfjJ\nXlaeEGaa5OxCXK1dAXjl4CuEZ4azJiCK+WsCKdYo/5abAuN4+e/zvLz+fLkQ1e9mdKeLZxMiU/PK\nlSW/UfQPVD2vHHqFZ/Y8Q3R2NNlF2QxZPYR5e+bVqlTJhRQlR6Uif8tY77FYmVox2HMwU32UN65u\nrooCtKDXAmZ0mMn2PZPIufoyeRFziU+9se9YQ1HfTtsYwDCUpAUQV9ngNsUlDJVO06lQaBWPNhNO\nu4+a+DMpMhAyojCP3EzrMQnEnvRE1mopDA3Fpl8/8o4fJ//iJayd8kQnJH2Waa6Bdtx5imjGcWEt\nfKPT3t07QdJlYa8vi7mVaOpRUE3Hq1UTkEzgyNfQbToOHp1oYmXG8qORjOnUFG/XamT6GqJP6Jr0\nNfR8pGbn6tBoZYYs2mdkPy+Nbrp/uYi6+XU0OLUqd25Uah55WDGx8AMysMPVzoK+bVzYcj6eq0nZ\ntHO3R5ZlvtwVQmhSDkM+21faTezlce1ZtF0Jn2zvYc+Cse15ZsUZZv16ghKtTCuDbNkd/xtCdFpe\nhRmuldHMwZpnhlfwd6sl/doIs1JbnaafmJeInbkdtubK3++F0b4s/EdRIq4kZDOgXRV1mqqBv7s/\nf4eKv3ttWtl9uTukdF3/t49My2Wo5zAA9kTt4XDsEVIuvo1eL/vgni58v+8q8ZnCpKN/M+vj7UxQ\nfBbZhSVM6NqMzPxi3th4kcSsgtKck7IERKRxKTaTRwZWHXMekx1T4f5lF5fRza0b6YXpHIg5QGhG\nqFH+QlUUa4o5k3QGPzc/I4Hfr1l55a21Q2t23bcLWwtbzCQR5fRf2H/8X9f/Y9R6YT7t7TSFB5eI\noAy52BlNsTNvbrrAP/MGVXtODU19C/wAwEeSpNZALDAdmFHZYGu5mB8svuFUifGX6KS7N5O6PAwr\npsLON7FsApa2WWTpNPomEyeSf/YsxZFX4aouMuG5QHBurdTGuWsx9NF5zjMiRRNsBy94dKuom1NZ\ntqjv2Jp94hFvwu63RR0ej07YWJgRm5HPQ0tPcOTVGlZ4zE0RZRNuUNgDRKTmGgl7gKyCYmRZFq+1\nLfuI5iSG5Yp1ROri2gvcuhGTlMPv9/nRysWGLefjCYhIJ6ughP3BSey4pNhdk7ILWTixE9P7tGTH\nxQTOxWSy/LE+DPUVXcYeHeTNzwdEWJyXgcC3szSjY7Pa1fxe8URfo1IKN4JW1tLWzY5Pp3alfxuh\nDSfmJuJhYxwx5GJrLNwvx2cxoJ1rje719IrThCXn0srFhrZudrw0tj19m/bF3MScdwe8W6uyCIZl\nKQAm+TXn33NxFBcrv/NCTQHWLX8nP/oxnhzShpn9WuHf0pHYjHzORKaz83IiLZys+fbB7liamVJY\nokGSpNK/W1RaXqUC//6fxJt3O3d7Bvlc//cSkyME/t779xKbE8uOiB0k5SWxP2Y/6YXppePOJp6t\nUODrNf+yvy+9CWdGhxlGAj8324Vjqanl/EWOVkpOi7+7P/7uQml8b8B7OJp7cN9PR8kr47COy2yA\nMui1oF5NOrIslwDzgB1AELBWluUqu2n/ZK5ke/rbeBKbEwtefY3GmFkq9noTGxvMmzenONzg1fAb\nf/J/e5HCg6uQtRg7WPWldVv0FLVnOlWjtG91GTRfNCHRlWRI0HW+is3Ir3HpXU1OMoUWN67lgdJy\nEcDMROKJQa0JTsgmxrDsQ6v+FdYLik7Lw87SjL/nDuCF0b4M9nGltastDtbmvLbhAvf+cJRv9pZP\n3390oDc2FmZsfHogR14dUSrsAXwNYuG9XOqu8QjAwHau1SuQVwnbI7bj94cf8TnxPNDbq3R+iXmJ\nuNsYJ5i1b2oc07/iRFSNTBzFGi1bLyQQnJDNjkuJ/LD/Gq1f28r8FRGcnBFQWirhRpBlmYuxmdxv\nUONfvx6Rmss3w7/B2aI5moLmmNmFIJlm01nXx7mLpwNjOzfltbs6sm/BMP58vC+ONhZYW5iW1oVq\n6SR+L9OXHDfKdNZoNWyP2E5yjvLdmvmrsfmvImKyY3C3ccfNxg1/d39e6fMKnV07k5SXxK7IXczs\nOBMQIaUger8aFoib8+dpHvj5uNE1k/KSSv0AK4NXciHlAr5Ovnw74lvu/v4ID/5iPH7rhXjiK2la\nNMVnCglJLcgr0mBmIjF/lA+/PdILeyszkrMLK/VzNEbqPfFKluWtsiz7yrLcVpblD687uLk/vJPJ\n0peeYaKlJwtS0/FwbENEZgRXcuPAQvdPNvRVzO11oY6SjGPsO1jZJJN3Mbi0iGVRjikRi7YS9sFO\nUqNbKw5VgKa6iA5NPVWzdO8I8edBlvl0qhI9svZUBdmtlSHL5EYFcjRe5s9jETz828nr2jBlWSYg\nIo1ijbHjWp99euL1kYR8MJ7Ruth2w2Jkhiw/GkGUrmlMTHo+LZyscbAx57mRPpiZmiBJEj7u5e3s\nfVs7s+zR3hx6eXippmViIpUrZ9HZU3mwNHO48VZtdU1BSQEvHRBhdfrQPT2JuYnlSia0dbOlY7Mm\nONqYs2hqN8JTcvnlUFi5v9GFmEySDNpdyrLMTweu4fPGtgrncSI8jdBaRnVtv5hAWm4RvbydsDQT\n/+LeugCC9/69jGlBF/z4BG2qyP40sUgtDTCoDoZa/faLSsmHDVc38NKBl1i4/yusmq9GMhURVNdz\n8oPIXG5hZxx2amjOeqLrEwAEJgfSdXlXevzZg4kbJ5JVlEWJRsvOy4mcTj7GsNUjmbRxElfTrxKS\nHkJZXuj5glE3MH1GdlZBMU+vOMPsX09WOsdz0Rk42ZgT+uF45o/yZUQHD76fIcpz6AMRbgUaWbVM\n5ZXs46kbIS+Vz0PXkBx3iPv+vQ/31q3Zbd0VqZkfTm3zMLeVsHXPxcQUrC1jycpwID/ZgtwsNywt\nFGdTdkpTXA3rtfuMFRmntTCVXBefMaJ0cfw5Hujtz7ReLRnwyV5OhqcxvU/1usunXz2JU0kqEXIv\n3tXZilNzi0qzTsvy95lYFqw7xwujfXlupBJLH5mah5W5Ce72lkiSRGudQ3LL+Xj6tnE2spln5hXz\n9uZLvM0ldswfQnpeUWm9IkMe7OPFqch0/Fs6MrVnC3p7O9GsiXgwVEWHpk34ZXYvNFotpjcaN1kP\nfBbwWel6eGY4AN+c+YZfLvwCYBTGB8J88M8zA8ktLBFRCH/DJ9uCyS/S8L/Ritlh0neHcbWz4PAr\nI1iw7hxbL8RT0YvAxG7N+O+8COe9HJd1w+atpKwCVpyIwsnGnKk9WnBX12ZoZbC3NMPN3pLL8VnM\n/k0Itr7tvbkMPDvGBf8KSkVXhoWZCe9P7sxb/1ziQowIsCgq0bI7VETuHE5dibkDDPHqxc7j7TgV\nkc7A65i7YrJj6NvM+A3eUOC7WLvw3oD3WHh0odGYqKwobGkNUiHWLVaQWlhEaiFM2SyyxC1NLVk/\naT3bwrfR3rk9A5ob19o6HJrCuC5NS0NMQ5NyWHYkvEK/Q1J2IZ5O1kZmow7NhAJ6JSGbAW1rZs5r\nKBpVaQUjzK3BoQUPdXyo1G6XVJRB1viPoVV/JHdf7BduRt80xtxGaBGRe11JOSUTe1T5whSERhLU\noSPJ3+jq3ZiawbiPwc24JvXR2KNkFmbWatol2hI2SbmEmpvD1V1QnI+E6Ht7IjyNEk31kkuOHRNa\n5nKNElp4JaHylPgrOi1j5Yko/jgWQVaBeHuJTM3Dy9mm9Ivqbm9FEysz1pyK5ts9whyTV1TCgZBk\nknMUTfSjrUGk5xXhVIHAn9qzBWfeGs2mZwYyq18rOjRtUi1hr2d0Jw/GdWmY8rCVcSZJyRHQOxE3\nXd0EgK+TLw91fKjcORZmIorH8KH49Z7Q0ugkfT+ElJwinllxhv/Olxf2K/+vLy+Nbc/X07tz6k3h\nHCzrczFEo5Wvazrq89EeDl9NoZe3M2amJthbiWglExOJ3x8xLvswzb8bEhIW1jVv+jKrvzfdvRyJ\nyRBvg6sDojgUa1yZNCBrGR5NLPlgS1Dp99GQZReX8fmRNSTlJRnVAwKw173N6zX/SW0nMddvLtPb\nT6edo3DUX0gMYfji/ZjahiOZlDervN73dbwdvHnK/ylGeI1AkiSjt625f51m35Uko0ztd/4tXyM/\nu6CYKwnZOJUpde5mZ4mzrQXB8bdOqYrGK/B1NLVtyt93/82CXqLGSHJesrC7zwuAFr3gf5dh2p+Y\ntfIpd65NN19avq+UQkj54Ue0ecYhkvrsvoyCDObsnsPLB1++4blO3jSZ7n92563z33Nvi2asC/iS\nvI+awYFFXEvKITYjnxzRn7wAACAASURBVI+2VlzFsSxm6Vcpkk2JlhXb8YYzImpibUA0+68YJ74k\n6bJaE7IKWPjPJd7ceJGsgmKOXkvBr4Wx9vbxvcJBre/z+8jvATz828nSsE2AEq2W9NwinCup51+R\n5n8rY/ig3x+zn7DMMFLyU5jSbgorJ6ysMFmpMgIihACNNvCf7NFpkfOGt+OHh3rw37ODeGtiJwa0\ndeWZ4e0wNZFwtbPEzd6ywjDey3FZDF+8n7avby0XFqvnVIQiuNu6lTe7dWrWhKeHteWvx/vyv1G+\n3N3NG18nX6OHXU1o6WRDeLIIClh5bi+mluIzavI90RQ0p0QuYeEkH4ITsnj1b+OQaVmW+fz05yy7\n+gEycjmB396pPX2b9eWr4aLXhJmJGc/4P8Mb/d5gzYS1WJnYs/KCyJA1tQ4H2RQnrXH0zb0+95ab\n84BP9gLK9/eZFeKz21spFoANZ4yjhqb+eJTYjHyjZkog3vI6NLUnOFEV+HWOvuFvUn6ZDD8HT+h0\nN5adjKNsLFq3xvPnZdhMfgz7sUqkTfqataXr+6P30+uvXiwOWExwuhDE+qp5VfHX5b94fu/zBKUG\ncTDmILnFueWKMr3n6sJIL0+04Qfo3kpU8vztSHilBdW2X0xg8neHmbfyDKSEkGTuyZSeiikhIjWX\nqNQ8Xv77fGlTFxD/PBdijd9MNp+L44llp8gr0jCjr7EZaUK3ZnRr4UB+sQZZljmpa+v3wRbxSt6x\nWRNOR6aTnldcoYavJ7c4l5/O/URUVlSlY24FUvJTSM5P5tnuz7J6gqgxs+jkImRkxniPKa2ffj3G\n6Hwjvh527LqcSIlGy29Hwo3GzB/lw4Kx7bmrazO6eDrw+KDypoOWTtasPRVDXlEJWq3MqYg0Rn1x\ngDc3XSj1uxwLS2X7xQQ6LdxuJOTv+0np0TCmc/k6RCYmEi+P68AgH1eeH+WDuakJnV07czHlInnF\neawPWc+llEuk5Kfw4fEPic5SfE6yLPPm4Tc5FKP4N/q1cSEus4DBX6wi2lyYvvJjZpIX8Sw2eSIw\nopOXltn9WrHjUiJ/n44hLCWdRQGLCEw27DMhlQuVtDG3YemYpUadoTLziskpLCEqrYDszJaEFxzG\nwnUXrh4hOJh6kxI+leyQMuW9DTgelkqJ7u1ozpA2uNpZlkbdbJ8/hK+ni6icF9aeY/vFeNYGRNPz\n/V2l2dwV0b6pPSEJ2Wi1MiUaLetPx5TzozUmGpkNv3L0GkBEZkQ5WxyASet+tJu8imyXx3F8/kNM\nLJV/0hZff4VcUkJwl64URSne/d1hO3BPKmK5djnLL4vCSdUJhdNoNXwa8CkAe6OFxvDJYKUm3IiW\nI0r355iYcFqTz/czutP1HVGr49PtwTw2yNvIfl5YouGFtYHkFWmwij1OO/NYMmzb88m9XenfxoVd\nlxO5EJvJ57uUB9KcP0+x6D4/vtwVQlhyLnOGtDFq4n4yIg1JokL7bOfmTVh1MprHlpXvfzp3aJvS\n19zuXpXbdvdE7eH7wO+5mnGVxUMXV/l7a6ycSxJVQvs260tn1870cO9RWu5Wbz6oih9n9kQryyze\neYWfD4TR7o1tmJlITOjajC26qpvNq+Gk7uLpwJmoDJYeCmdNQHSl5p25f4l+ET8fDKOXtzMZeYpJ\n451JnUpr+1eFg4UDucW59F2p2NDNJDNK5BJWX1lNR+eOTGgzgd5Ne/PPtX84EHOA/dP2cyLhBIN9\n/AANtm2/LD1395x5TPjmEG/fNYjXj/9FdHY0XVu0QXMskhfXnaNH+2RCTf7kz8t/lp5jUdymnFO8\nIvze24m7vSWfT/NDW+iOZH8ZS7c9ZGugr8tkdhdpAFuyr7zDgLbG0VqyLDN9iRKZM7NfKzaciSUl\npxBXOws8Ha1p1q156fd+7l/l33rmVFBxt0NTe/KLNXy9JxRzU4nFO0OIy8g38qM1Jm4ZDd/DxgNL\nU0s+PvlxOU0agB6zMX8zGOeXPjMS9nokMzOsunUjY9Vq0levpiAkhLbrT/HlLxo80hSbaEp+SpV2\n/IisiHL79L1F109az9cjvmbrvVtLm1l/J6dgZ2nGrH6Ktt7+ze2cjlRijJcfjSCvSMOzXhGssXyf\nNiYJJFl4YWZqwtSeLfB2tSU2I59/ApW8tR2XEll+NIJluiqTM3XXtzI3Yc2T/RjW3o0/HutT4UPs\nMZ1jat8V4wYZb07oaBRG2atV5YIjKFW8Eeibc5Roa1kkroEITA7E3MScjs6iGJlh2zs3a7fKTjPC\n1ETC3NSkNGQRRHet8V2bYm8p9KrqJN4tGCs02n1XksoJ+4oa+Oy6nMi4rw6WfgcAfJtWXQZaj750\nsyElsvJ3DEoLYvGpxeyJEsXjMgozGL52OHN2zSE05wS+vueMzvV2teXSe+MY3lqUKghOC6atmzWY\nCNv5pf9v77zDoyraPnzP7mbTG2mEFELovYpIFVBAUEBRQEUBCwIW9MVXsaN+dn3FhgqK2FGKAtLF\nDgKCUqWTEEpCSO9td74/zpYs2UDCppK5r2uv7M6ZM2d2Z/PsnJnn+T1JZeMu8/ICKCg+vyfPyl3a\necnZhdz/9T+YCx3dZIc3KxUvY/bAU+/j4DG1Ypf9utufvApvdwOeRm3CZV2b1+kEG2cOIMyvrP14\n+YaOTjfS+7XUvh9vbTzM6+s1z6C9p1zbB6xO6o3BF0LY9D9m/TbLVm4ym3hv53usiVsDvmFl9G02\nn9pMx087MujbQQQ+rGUmSpr9LHEjR9Frg7ZW986HJmZ/UcIrC0rwy5WsXus8ufSh9EN0/LQjo5dr\n0sClg0Csnh3WTERRvlEsvm4xT/l14m8D7Dq7i+dGtWfhZPvG2feWSMZik5lPNx+nR9NA/tPW/mXJ\nMDa2PbeG+4OmE7/+of4ANrXImCAvohp5se3xwfzx6CAujw1i4eSeti/kubQM8+Xru+230daE3v1b\nhTjk4fU9T84Ba8DMrrO7WHl0JV0/78o3B74pt35lySnKYezKsby54022JZ7fLdUVdp3dRfug9hj1\nZZevrNmRKkrpcbqucxP6tQxh9Yx+rLyvL5fFXHjW7efhxs09o/gnIeOcfgiW39eHQ/93je0HZGwP\nbUPzQFI2C/7Qvn8RAZ6V8rjpEtqFuYPn2nzdQZMZmNp5qkO90hrx1mCopzc/TaLevkT6en/7XZ6P\n0Ydo32j2p+7nhZ334N38DdDlYdbbv99+mVPpFXwtBWeGceA8DgnFJjP3f/2P7XVGXjGy2P4eB0YN\nZGSbPkzoFc2CSZrI3MYDybY9L4CN+5MJ8jZy7MXhNk836+dUehO8eYgPY7ppn+vd/ZrRJSqAqEae\njO7quMdgxVng2U8Hki9eTqWaqTdLOgA3trqRJYeWkJyXzM7kndy9/m4KTPZdd2tWmfd3vo9O6Lin\n8z08+Itm5M/mn+VUcz98evQgb/v2Mm23syxXfvS2CfiCwk634N7McY319jW3O7z+5tpvSMhKYOnh\npXz272cAZZJRDAnpxvNZu9l24je6hHahd/NghrYPY92+M3y+5Tjtm/iRvPcn9JlmenTujbDkyv2q\nZCBXXz/N1o5VVKxrdIBNJ97Xw8BWy/r7G2O1GVWon0cFP00I97fXnX9bd46l5NIqTJsdrnqgL9kF\n55+xp+WnEekTycmckzz+hyalvOTwEoecrq7wZ+Kf7E/bz/60/SzYu4Dnej/H9S2vv/CJleB41nH2\npOzh1jZ2L5zYgFgAByNYUa6IDeKlGzpyWUygLeGKv6cbUZWIBys9k/zzsUEEeBpJy7O75H53b29O\nZRTQtrEvu05kcvBMNlkFJTTyNlY+mhvoF9mPfpH9mNljJnqhRwiBWZoZGDWQlgEteWrzU6w6tgqA\nV/u/yvN/Pk92cbbDnfDAqIEMbeYYld42qC1/nPqD3OJcdAbwbf0cANLsRs7B53huXBc6RgSw4fdf\neWn1fqZe2ZyBrctmUJv2xY4yZZ/dOpaNZ9OZ2H6izWX2/0Z3dKjzxdbjXNe5CRM+3sq2uDRu7hmF\nrpQr8NPXtsMsZRljfmP3SHYcT2dK/+Y8MeLC+zcGnbDtDYB2Z/fA1/+wdFrvOpdEvt7M8EFzs7q/\n6/2kFqRy25rbHIw9wEtbX8JkNjF311ze3fkuxzKPOaSCi8uMw7OLox75iQ72L5gh1P68OCGBwmNx\n5O/ahSwupthUbMtTaauvMxAbEMt/L/svE9pOsHkUlCbAvyk6KXln73wSshIwGnR8eJtd6vbQ8ld5\nIGEGC91eIcgDOPEXXD6VW/7ve0KC7aHfbcP9WDSlF5/eYRd+en6UXQ+/U2TFZ3VWwgM80AntxyRH\nnmZxwovkFWszk/ZN/G2aMuWRWpBK59DO3NvFLp98IO1AlUjcFpuLyygmrolzHqxUGbKKslh5dKXt\nbuH1v16nxFzCqBb2aOsxLcewcvTKi1JCFEJwc8/oCmXXKo/SBr+xnweeRr3Dck6LUF8GtAoh1M+D\ndZY7PQA/D9fmbwadwR40J3S0C2qHm96Nl/q+xAdXfcAHV33ANc2uYfMtm2nub1/PXjhsIW8MeKPs\n+2jUtsz/DIBBb+boiyO4vmskoZblk61xaUz+pOx+EsCP+zVHjavahvLqmE5snjWIPi3CePqKp8vE\nRwBMu1Lr2z8JGazcddrmlNCjqeOvrk4neG5UhzL7HbEhPnxzzxWE+FZMG2ntg/2Yd1t3Hhlm32D+\nOyGD534o6+JZ29Qrg++mc+P2drc76E6/2PdF7u96P6CFUK+OW207Nup7R8mEuMw4gu+9l6aff2Yr\n2/SfK4le8DGe3bsTvXChrfzEPVM5Nnw48ePGk/zmHNvyxaT2kwDKuJE92vNR5wkx/KMwW/6J3tv5\nnlZ29hDrjI9wjW4rI/VantNYXRJ3HH9ES4Qe41yMqVdskENax9FdI/j8zp4smXrFRWnIuBv0/P3U\n1Xx2R09e/etV1h9fzx+n/qjQuVJKUvNTCfYIZkqnKQ6BMxPWOJ8Z5xXncSzjGH8lOf/HTsm3C90t\n2LOA7498T7fQbnQN7Uq0b7TT6MnKsC91H+N/GM/jfzxu01Y5nXua3k160zLQvsmmEzpi/GNcupYr\ndIrUvt8RAZ4VmiFa91lKK15WJUII+kT0oU+EXRbY6ic/puUYuod1L5MdCqB9sKbPdO7/yqDoQbag\nO+vyVHmUXtu/7YoYxl4WVa5+j5VHh7WxLdfMXGzfY7Cq11Y1LUJ9GdK+MdOvbMHSaVcwuksTvI16\nPtkUT8ysVTb357pAvTL4AB4GD5th7RvRl+uaX8foFqNt/7DPbH6mzDk/3fQTTf2aEpcZh87TE6/L\nLiN4+nRW9PfAQ++Bd+/exHz5Be6xzfjpnbLabmkLFvDER1o6u6ubXs27g97ls2s+K1PPKWHt6Zen\n3WXk5VpcSncspLXuJO8b36KLzu6iqY//VRN0a1lxHfd+LUPoEXPx+jEBXkYCvY22Ddd/kv+5wBka\nj//xOAWmAqL9otEJHR8N+Yi1Y7TUi0m5Sfx9xtHLQUrJuB/GMWr5KO5Yd0cZo78zeScDvx1o0yD/\nMUHzsX6h7wt8ds1nTGw/kdSCVKfZms7HvpR97Dq7iy/3f8n4H8ZzIltbu7P2LyU/hSY+TSrVZnXj\nbtDz08wBLJte1hvNGR/epuW3nVGDniEH0jQ35h6Ny0/Mcnnjy5k/ZD4rr1/JxHYTmXPlHFbfsJpn\nrrD/jwohHLbdzs0Od/Ss5hL57i1dHZwJLsTLYzqWKWtaxdpNzujetBFzxndl/X8G2MqGvPkbu05k\nnOesmqPeGXyA3k1642nw5MZWNwJaAollI5cxqf0kis2OEX2T208mxCuEZn7N2JOyh5wi7QsU8sD9\nfNtPh4fBcc27UZNY2/Pnx+uYNl1PgRtM/D4LpKSpX1MGRA0oI6ZVLu4+zDlzlu75BZw8uVnT70lz\n9DJa62sJEInpBw/uBoN7jXu8WD+XpYeXsjN553nrFpQU2ISsYvxibOURPhE82E3bM3ljh/0WP7c4\nl6k/TnXwbvr5hGPSkK2JWjDR3pS9pOSncCDtAONaj7Ol9hsaMxRfoy/zd8+v8HtKzU9l/KrxTFg9\ngZe3OaZS3pa0jWJTMWkFaRX2xKlJYkN8CKvgfkyQjzvHXhzO2MsuIqn9RWLVlB/StPzJiRCaf72b\nzo2HL3uYwU0HE+UbVSYz1Ds3d7XtT2w95hj1+/Hv2mZ0Cyf6TefjXI+mDQ/1r1HtpogAT3Y8ac9K\nN+q9TVWWP8AV6qXBHxozlG23biuzhGK9hSzNzW1uBjS966TcJEYtH4WUEpPZRJG5qIzBb+JnF3E6\nFCFI9Rd8NlhH9FlodoaLSmNm1LvTubCQI0Yj6zfOojh5H0WthsHgZ8iM6Eqfaa/DpFXIWxaz5PBS\nun/ena6fd7WtWecW5/JP8j8V9lJZemgp/Rf1Z3tS2c3p8sgozMDXzZf8knzu3XgvRabyFQCXHFoC\nwMR2Ex0SdgBM7jCZQPdA9MLu3bJw30I2n97M4OjBzB08lz5N+rDk0BJMZhPbErex+NBi0grSbP0Y\n+O1AAJs8LWif+5CmQ9iWuI2CkopJ0p7KOVWm7IrwK+ge1p2/k/8mIVsLGDs3X2x9RFfDukSv9X+N\nn8f+7NSzqbJc26kJGy0zYuuMHrRI5WUWT7aYSoi7geZdtuWxwXx6R08WTr6MlmEXv6dysQT5uDvs\nx5zOyLcJttUW9dLgl0czP82rpkVACxaNWMToFqNtM/HeEdrtcXJeMnGZceSVaJuTHnpHgx/uE87f\nsYIzAeDhq60DZnfX3C/vlheZ6OC+bXSP1FISzkxcz/U+xYySCci+DzEmwMDwFaORTfuwK+Mgz/75\nLEVmzdg+8tsjZBdl89m/n3H7mtv5YNcHFbrc7D9nk16YzuR1kyu8gZpekM6oFqN4/PLHySrKch7r\nYGFN3BraB7VnZo+ZZdaYdULHgKgBnMq2G9sN8RtsYfL9IvsxJGYI+SX5/HLiF+5cfyfP/fmcTbfG\n+lcgGN5suEPbQ2OGkl2cbbs7SM5LpuOnHZn5y0yHekm5Sfx+8ndbIhErT/V6inlD5nFTq5vILc61\nudc62/hTnB8vNy9b9qyqwN/LjQAvN1s0sZSSfq9q4zx1QHM83CrnHgvQ2N+DAa1CuNKJ509N8c09\nvXjmOi2u44stx+nwzDpiZq3inY2HHerlnvNDsD0+jVlLd1daUv1CXFIGv1VgKx7r+RgfDfmI9sHt\neb7P8zY/6l7hvfhupJbLdtqP05i8djIAHYMd1/oifCJ4eZyeR+/z5fZ2mhtmUNNWGJqE0/lQEfl7\n9pD900+V61hgDP1u+IIrQ7XZ8HE3N06W5PDbyd84k3eGjMIMUvJTSM4rmxh6wuoJtuTKiw4usmn/\nlMe5iZa3JG4pp6adE9knyCvJI8gzyBZ05KwvRzOOMnvzbHan7KZPRJ9yNxQjfSJJzk/mrnV3kZSb\nRFxWHF1C7LP1WH9t2ey5Lc/Zyqw/wFYGRg1EJxy/nt3CNDnaXWe1jbi71muyueuPr7fd/UgpGbZ0\nGNM3TmfZ4WUAPNjtQX666SfGth7rcH3QJgetAx1F9BS1Q6swX1vQUmmpkLbhNT87ryr8PNy45fJo\nvI16hyj4NzYcYnt8GgXFJl5de4D2z6xjjSUiGzSZjEV/neDI2fJlHS6GS8rgCyG4pe0tBHk6dye0\n+lefzj3NwfSDeBm8ymw6ebt58/WIr1l+/QqaB2juXZ1COuHTpw+5m/8k/qaxnJx+L+aiyiU9EELw\n4BVPOJRZ5RkAjmUeczCy1lnnscxjNs+ZtII01satZffZ3eUa/j9Pa378T17+JOHe4aw8urLcPkkp\nySvO46cE7QdsaMxQW2YnZwb/vo33sfTwUgw6A+Nbjy+3XesSydakrUxcMxGzNNsC0gDCvcNt76df\nRD+byFW4dzhfDP+CPhF9mNljZpl2rZo2X+7/ko3HNxKfGW87lpir/bP8fup3TNLu2fFKv1e4s+Od\nhHjZ1+lj/GMIcA/g6qZX892o78os6ylqh17NGrHnVCbZBcWsKaWzX5HE9nUZd4O+TMIcgKV/n6T3\nyz8x16Kt9dthzUuttGfSkDd/45b5W4gvJ39FZbmkDP6F0Akdi0YsonuY5tVQXlahDsEdaOzdmEFR\ng1g+ejm3tLmF4HvvdahTePiw03PPR6x/LP0i+vFYz8fQCz0nsk/Ylpxm/T6Lz//9HHe9O3/d+hff\njfrO4dwBkdoa56O/P8qtq2+1ebOcy6f7PsUgDFwTew2dQjqx48yOcjeAV8Wt4vKvLmfF0RWEeoYS\n5RtFkGcQBmFwuv5tlVBYe8NaBwN6LqVdHE/naiHtbYPa2spKLwVM6zyNGd1m0C20Gx8N+YjOIZ35\n4KoPiPZznjfAuifz1KankEjGtdaCvKx3Qecuew2IGsC5eBo8+Xnsz059xxW1x+WxQZglbI9PZ+3e\nJLyNem7uGVXp9fu6yKQ+zbgsJpBNswYR99JwruvchK+3nXDIluXhpuOFVf/S5qm1DuduPprKqPc2\nVUlmrQZl8EHb2F04bCHLRi7j0cvOH1gjhCDWPxYhBG6NGyM87bv8pozKu1kJIZh71VxuaXsLb175\nJnd0uINlI5ehF3pS8lM4nXua1o1a42HwwE3nxh0d7rCd+3K/l7mp1U2214/89kiZWb6UkqOZRxke\nOxw/ox/5JfmUyBKHsPjSLD64GNAkI65qqnkUuOnciPGP4Ui6Y+rCKeunUCJLmNl95gWFrloGtHQQ\nHZvUfpKDDIVep8dN50av8F50DOlII49GfHrNp+Ua+dI8fvnjTOk0hexibelqROwI3PXufH/0ewpN\nhRxMO8iYlmNs9UsnHi9N6SAjRd2ga3QABp3giy3HiUvJ5fERbXnphk41viFdHYzs3ITFU3vbYiv6\nl8rz2zzEm2Afd9btTWL+73aFVaun0aTeMWTmF9Pt+Q0u96NeSStUJaVnoRUl7PHHSHpKy7qTtXo1\nHq1bYwi+uI2rgdEDGRiteaOUXoK4LtZ+1/FQ94e4s+OdnMg6gY/Rh1k9Z3FXx7sYulQLYU/OS6ax\nt11v52z+WXKLc2kfpHkrWaMcrd4+m05v4sW+L3I04yi9m/R2CGR6sPuDtuctA1qyO8WuX55ekM6f\nidpSkbNEIOcihGDZyGXsSdnD1sStDj9cVv685U8HT57KcF3sdbYfsVaBrWjk0YhNpzbx9KanKTIX\n0Su8FwOjBl60QZclJRy/7XYCJ9yKz4AB6H0q5xKouDi8jAbaR/iz8UAyQmBLx3kpUtrldv7tPXhj\nwyFW7U50qPP13b3Q6UAnhE0cL6+oBC/jxZvtBjfDd4WAG2+k6VdfAZC5dBnx42+u0vaXjlzK+DaO\na+N+Rj+bu6lRb3QIErIGEVmxetZY9yqe6qVpg8dnxfP+rvfZfXY31353LTN+nsFrf71GTnEOD3V/\niAVDFzgk+GgZ2JJTOadsvvlWVcwbW93oNKLSGUIIOoV04u5OdzsVIHPXu2PQXdwXt7RXjbebN7Ov\nmA1gi7JuF9SOAVED6B/Z39npFyT9yy/J/+cfTs98mEM9LqPwiP1uJ/mNNzh2fdnEGoqq4TJL1HDn\nyABCfS/dvZV+LYNtM/imQd70s6SA1JaxtDvdxv4eRAZ60STA05YbOyHNNVE2lwy+EOI1IcQBIcRu\nIcR3QoiAUsceE0IcEUIcFEIMPV879QUhBJ4d7fo1xSdPYsqpul1064bphVgwdAGgCX8VmYp44o8n\nSMhK4N1/NJVPqxdK84DmdAjq4LSNbw9pKoe3t7u9jC+9NenEuzvfRUrJ2vi1+Lj52LKO1TbWmbs1\n72nviN4O+QhKbxBXFnNeHmdecgzSylq/3vY8df5HFO7fT8KUKRd9DUX5WDc3AyuRMrM+IoRg06xB\nxL88Ar1OMLZHFB/e1p0l03rzwugO7Jk9BKPBbp6t/vyf/BHv0nVdXdLZADwmpSwRQrwCPAY8KoRo\nB4wH2gNNgB+FEK2klOcXva4HCDc33Fu1ovCQthxy9u23afz44y612btJbzaf3oyfsWKJq7uFdsNN\n50ZCdgI7k3ey4ugKknKTSMlPobF3Y4co4BndZ7A9aTuTO0xm5dGVvLD1BYe2nM2yrUtCX+7/kr4R\nfdlxZgedQjqVux5eG/wx/g+HJaERsSPIKcrBqDe6tDaftca+Yebeti3mrCxS3n6HgOuvR+9nH5/c\n336n8Fgc7rFls1YpLh5rsvM7+8ZeoOalhU4nGNrevjx7riy5VcV2R0I6ruDSDF9KuV5KW7aELYA1\nZHEUsEhKWSiljAOOAD2dtVEfabb8e5otW4rw8CD9s885PuE2cv7YdNHtvTXwLX688ccKGyq9Tk+U\nbxSf7P2E93e9D2gRqmfzznJNzDUOdXuF9+K+rvfh7eZti0y2zoBLb26WprRb67Qfp5GQnWBzpawr\n+Lv742N0XFsf12ZcpeWTpcmELLbLcSQ+obnONluxnNjvlhEwVvPdjx9/M6kfa3dWOovht/7oK6qO\nJgGexL88gr4tqy6o61LAw03PjMEtOZKcw7zfnKdIrQhVuYZ/B2DVr40ASi8wn7SUlUEIMUUIsV0I\nsf3s2bPOqtQ5hBB4tGtH+PNa4FDe9u2cfuQRpOnibmA8DB4VSvFWGqtL6fYzmnxCdlE2Reai87YT\n4hXCxps2snL0SvZM3MPs3rPLrXt548sdXo9sPrJS/avLSClJ+/wLik+dImHiJA73H2ArF15euEVE\n4NFK8ypqNHkSACVnzpAydy4ATT/T0mEWHT9O/s6dnJzxINk//1z2QgpFFdIyTJvgvLj6wEW3cUGD\nL4T4UQix18ljVKk6TwAlwJfWIidNOY0RllLOk1L2kFL2CAmpeyJW58P/uuuIeOdtgu+7D1NaWo3O\n+O7scKfDa2vg0YXWr0O9QiuUxWn+kPm8N/g9BkcPZustW21RrnWZpBdeZH/7DuTv2XPeekXHjnHm\nhRc4cf/95G3fr9HduQAAIABJREFUjik9nYPdunP06iHIvDyCp0+31dUZjfgOG2Z7HTT1HjzatMEQ\nEkLe1q3Ej7+Z7HXrOPXADPa3aUvBwYPOLqlQuEzphEWZecXnqVk+FzT4UsqrpJQdnDyWAwghJgLX\nArdKu7rXSaC05YkEyiazvATwu/pqfAZo3iBxY24keU7ZJCjVgRACXzdtXc/Hzb60Udrf3dX2+0f2\nZ87AOWWyeNVFCo8cIf3zz8FkIufX385bN/Wjj7Vz/t1vKzPn5VF8Ust54HuVoyhf6MP2qF/35lp8\ngbFpU3I3b7aVW5eFstetR6GoDjpFBtjyBzz23e4L1HaOq146w4BHgZFSytL+QiuA8UIIdyFEM6Al\nsM2Va9VlDKGWZRSzmdQPPiThjrJ+59XB/KHzubnNzbbkIw/3eNjBL786yNm0ieyffkaazdWWY/ZC\nSHNZWYnCo3adkqKE4+Wem/3zz2R+913ZA272TTK9v2MovzEykpZ/bibo7rvxHarJAXt20+54AsaP\nc7gjMOfVzVymivqPm17HnmeHck2Hxvx9/OL09V310nkXcAc2WDYct0gpp0op9wkhvgX+RVvqufdS\n8NApD0Owo3ZP7uY/KUlPxxB44aTVrtA+qD3tg9qTXZTNbe1us0lGVBemzExO3KkJlumDg8FsptXm\ni9+svhjOvPoaaQu0zdM2u3chjJo8b+nltKJ45wbfnJ9P8quvARA59z1OTtfkMmLXrMbYtCmm1FTM\nhYVOzzUEBhI68z+21yEPPUjIffcijEYyvv/eVm7KyEAWF2MuLAKzCeHhgc7ouoSwQmHlsphGrNmb\nxNZjqVx+gTSk5+Kql04LKWWUlLKL5TG11LEXpJTNpZStpZSuJyOtwwi9nrCnniTo7rsQlpmis0Tp\n1YWv0bfajT1Ayjy7RIMpJQVTWtpFb1RfLNkbf7Q9z/vbnp2r8NAh3CIjCbjpRgp27yZrTdmvXMbi\nxRTFxRH10Uf4DhpE49mzCb7/PtybNUPodBhCQjBGVkwbXwhh+7Hxvty+wZ35/fcc6NiJQz16cKjn\n5ZycOrW8JhSKi+LGHtp39N6v/iElx/kEpTxUpG0V0ejWWwmdOZNW2/9CeHpy9s05WqKVrCwSn3qa\nwmPHSJ4zh/1t2jqs/dYXZEkJ6Z9/gTEmxqG85IzrCcsrgzkzy7aJmjBpErJE8wouOHQQj3btMDbX\nFE5PPaTNxgsOHODEvfdRcPAQZ158CQDvPlpuhMDx4wg5RxTvYnALD6fN3j34DBpU5lju5j/JWre+\nxn8YFZcu1rzWKTmFvLmhco4iyuBXMTp3d4LvmULRsWPEjx1H6oIFZCxezLHhI0j94EMAEu648wKt\n1D1KzpxBFhXR6M478L/+etwiNC/b4sTEC5xZdUgpMWVnY2xql1YoPHKEs2+/TfHxBNxbt3I4dnjg\nIOJGX0/Oxo3EjdKcygxhYdUimiYMBoLuusthL8DKqRkzyNuxo8qvqWi4PHiVpgW2+Wgq2+PTLlDb\njjL41UDghNsAKNizh6KjzoMkihISSF/0TblrxnWNolOaXLIxIoImL71I5LvvAFCSmmqrU9kcARWl\n4OAhcjdvxpybCyaTw6Zq/q7dpMzVgs+8elyGWxO71lDJOT9GbhERtPil+vzlvbp1pe2e3TT96ssy\nx0zpdSOJteLS4MGrWhEZ6ElcSi43fvBnhc9TBr8a0Pt42wxi9oYfcYuMJOxpTcjMy7Lee3TIUJJm\nzyZ1/kdk//JLbXX1gkgpOTrsGhJunwg6HcYWmluivpG2WXTqgRmkfrKQnN9+42CnzhQcuPigkPI4\nMW0qCXfcyZFBmruk3t+P5uu1fABpCxcC4NY0Gq+el+HeqhVeV/SynevRwa4l5N6qVY1IInt160aL\nX3+h5R+/28rMVai5pFAAXNOh8h55yuBXE57d7ZuoXj16EHjzzcQsWUKTl19yqJfy7rucnDoNWVJC\n8ZmyWaZqm+KEBIri4wFodNttuIVqOj2GRnYPpORXXiH9q68BOP1I2RwDBQcPcnbuXMwF508+XnDo\nEOlff03W6tUkv6nFM5gyMig5rc3UzVlZ2rWDgzFGR+M9oD9FcXHo/PxotmSJtpEqBKEzZtjajPn6\nK8L/73kABwmF6sYtLAxDcDAtN2nZysw52Rc4Q6GoHI8Oa8N303szuU9Mhc9RBr+aMAQGIry0gCW3\niAhNabNDe9zCw/Ebqcki6Eu5bWZ+/z1HBgzg1H8f4eSMB2vd+BccPMSx62/g6FB7lGnof+1qmcLN\njaC777K9zrHcpRQeOmTboDzQsRNnXnuN5FdeIeXtd8jdUn5+XSklcSNHkfTsc5z6z0xSP/wQU04O\n+fv2AdjukAAM4Zquj1c37UfVb+gQ9L72FHJulnV84empid21sWTbqoWEJ/oATUC2KlVVFQoAg15H\n1+hAnrmufYXPUQa/Gon9/js8OnYk4EZHkbLGTzxB7MoVeHSyJ1BPfFIzaFkrV5K9bh1527bWaF/P\nJfUjTQa4NMLgGLYROnMmIQ8+yLkcn3Ab+bt3I4uLSft4AUXHEwBIW/CJzasmb8cOiiyRreBciKzo\nyBGSX34FhMDvGrsonHWdvtHttxH25JOE/Oc/DucZAgOJXriQpp8uBMCjXVtCHnqIxs88U9G3X2UI\nvR7h5YU5Wxl8Re2jDH41YoyOptnib3ELd1Sa1Pv7496yJf7Dh5d7bk27O1qRJhNFJ0+h83C3lQVN\nvYemX3/ltH7w1Hvsz++7D4D8f/4hfuw4W3mxZcM3b9s2zr7zLgUHDnD81gkcvepqm+5N6SQjVtK/\n/prCw4cJnfkfhyA2awYqnacnjSbc6jTAzbvX5Xh26gSA0OkIvmcKxkin+n3VjiEkmKK4uAtXVCiq\nmQab4rAu4D9qFB4dOpAy932yVq0i6J57SP1Qc92sjSUdaTaTMGkyeX/9ZSvT+/sT6mQWXxpjTAxF\n8fEE3zudvB3byfuz7NKNsVkziuLiyF6/3qZZAxB/01iC7r6LzFWrAGg8ezaFhw6R/tVXZC5fAUCj\niRMBiF74CTrv+pdu0PuKK8ha+UNtd0OhQNSWHoozevToIbfXYIRqXcFcUIApM4ui+HgSLMbN0Lgx\nnp07E/rwTIxRZRUwzYWFFB45gmf7iq/flUfhkSMkPvU0Ok9Ph6Cw5hvWYwgNRefufp6zNckFU3aO\nbQad+vECkl97Db8RIzAEB5O38x+aLlxIxrffatmkDAYoKSnTjlfPnjT97FOklBxo2w4AfUgwrX7/\nvUzd+sTZuXNJefsdBykIhaIqEULskFL2uFA9NcOvA+g8PNB5eOAWFkrztWtInP0seVu2kJ2UBFIS\n8cbrmHJyHJYuUua+T+qHHxL9yQK8r7ii0tc0ZWSQ/fMvyOIicn75lfx/7DIFMUuW4Nmh4j8ken9/\nB994/xuupyghgZAH7scQZNf68O7bV3tSUkLQ3XehDwhAHxBoSzoSbIl6FUKg8/XFnJ1N7PLllX5v\ndQ3rZ2PKyrropPcKRVWgDH4dwxgTQ8gD93Py8GFMqakUHjtK4pNPkrl8BW327UXo9ciSEjKWLAEg\n+6efyzX4JampFCUkUJJ8loJ9+/AfeR3o9RgjIjg6dBimzEznfYi++JywoG2ahj87u2y7sbEId3dk\nYSGG0DAa3TbBIVLXs3Mn2/Pma9dQePQohkaNXOpLXUDvr3nqZG/YQMD48TUSC6BQOEMZ/DqIV7du\ntNr0BykffMDZOW9RdESL1jVlZaH38yPn998xWSJc0z//nOApd2M4J3lMSUoKh/v2cyhLLSV+di5R\n8+dx4m4tMbeulItjVSKEIPK99zhx1114du0KaDo0rf7aRvGpU+g87AkeDEFBDncH9RnrDD/p2edA\npydw3Nha7pGioaK8dOownl0ds0yZ0jM4MX06J6dp+utePbU0wTm/lV3jzlq3zuG1tyVJizPcW7fG\np5/9x6E6Z6A+ffvQZs9uhyUjva8vHm3aVNs1axtjjF3fJ+mZZ0iZN78We6NoyCiDX4fxOGdDNu6G\nG8gtlc0p4q05IIRtWaT0Bnz+Pzttz4OnTyd89uwy7RtjYoheuJDY5Zqee/TCT2ySENWJcCIwdilj\njIrC9+qrbK/P/u9/tdgbRUNGLenUYfQ+3hibN7cJsMlzpAkMgYHoGzUie91agqbcTfyYG/Hs0oWw\nJx4n948/8BsxAv8brserSxd03t6atosQCIOBkuRk3Fu2dGjPu1cvFNVD5DvvcGzUaAoPHkTnVfdT\nRiouTdQMv45jzbJkCAsj8r138R81EoDIuXMBcG/enMLDR0iYfAeFhw+TsXgxB7t0xZSRge/VV+HT\npw86b2+tjeBgDEFBtsAvRc0S+c7bGEJDQaertfSQioaNMvh1HN9Bg4hds5oWv/yM7+DBNHnlFdoe\n2I/voIGAZkQA8p3orZ+7B6CoXYzR0QTfey/mnBwK9u6t7e6Qt2MHGUuW2H58io4f58S06ZgsInWK\nSw+1pFMPcG/WrNxjen9/DCEhlJw9i++wYXi0boV727YYAgNxCwutwV4qKoJ3nz6AFmEcOGECjZ98\nwqX2zIWFFMUfx6N1q8qdl5vL8VsnAGBoHI5P3z5kLF5Mzs8/k/bpZ4Tcf59L/VLUTdQM/xLAmuXJ\n2CyG4GnT8L3ySjw7d67dTimcYoyMIPB2LUFO+hdfYMp2TTb5zEsvETdqVKWlOEoL1yW/8gr7O3Qk\nY+ky7VhCQql6p0icPZvi06dd6qeibqAM/iWA3whNhM2j9aXr2ngpEfrwwzaN/rNvvulSW1ZvrPxd\nOy9Q0xGrUffo1InCw4ehpARTejoAhQcPkrlqFWdefY2zc+aQsegbUj/6mNwtW5AmEzm//krym3OQ\nZrNLfVfUPFVi8IUQDwshpBAi2PJaCCHeFkIcEULsFkKoxeRqJGD8eFr8tBHfIVfXdlcUFUBnNOI7\ndCgA6V99TfqiRU7rFfz7LwUHD563LWtQV9aq1ZXqQ/EJbYYfOG5cmWOFhw5xeubDpC1YQNYPP1j6\n+RUJkyYTf/MtnLhnKqkfflgn9iEUlcNlgy+EiAKuBhJKFV8DtLQ8pgDvu3odRfkIIXBr0gShUzds\n9QW9ry8tfv0VgDQnSzuypIS4ceOJGzWanE2bnLYhzWZbHoHsdescVE7z9+3j5EMPOc3yZcrOJuXd\nd9H5+ODRvl2l+l2we7fteUlK6nlqKuoiVWEh3gQeAUr7mY0CPpMaW4AAIUS407MVigaKW1gofsOH\nU3TkKAkTJ9nKz779Noeu6A0WY31qhl2eWhYXU3zqFKasLI5dNxJThj05etpX9pwFx2++hew1ayk6\nYV+rt9X75BPMeXnoAwNxi9AUTj3atSN64SdEvGkPCmvx808E3X0XTV5/3Wn/rUtAivqDS146QoiR\nwCkp5a5zwvEjgBOlXp+0lCVyDkKIKWh3AURHR7vSHYWi3uEzcCBZq1dT8O+/HOjWHZ2bm4OonTEm\nxpYe0VxQwMEuXcu0Yc2jkL1mLfJ//0MIgSwqAiDpueeI/vgjhF5vq1+w718Aoj+aj97Xl8i5c/Hs\n3MmmXeTesiWmzEzcwsMJnTkTAN+BV5L2+eecnfMWQVOmkDpvHolPPIHvkKsd0ksq6jYXnOELIX4U\nQux18hgFPAE87ew0J2VOI02klPOklD2klD1CzhEAUygudfyvu5awJ58EQOblORj75hvW43/DDZhS\nUihJTXUufqfTEXLfvbaXxyfcxqn/zLS9ztuyhdxSS0KZP6wi59dfCbjpJpt3l++ggQ5Cde4tWuDV\nvbvjZby9CbrnHpqtWE7IQ/Y7jkOX9bzId66oDS5o8KWUV0kpO5z7AI4BzYBdQoh4IBL4WwjRGG1G\nX1pjNxJQfl0KhRN8rxoMgLF5c1tZs++/wxgVZZO+zt2yheyff8GjXTsaP/ssAGFPPknrHdsRbm6E\nznoU0ALwslY7buCmf/stoPnen35YS0RfWtunoggh8GjVCiEEnl262MrNlrsJRd3notfwpZR7pJSh\nUsoYKWUMmpHvJqVMAlYAt1u8dXoBmVLKMss5CoUC3Bo3pu2B/TRf9QPhL/wfUfM+tKmHurdsAcDp\nmQ9TuH8/Hp06EjhuLM3XryPw1lvQeXoC4DtwYJl2Q2Y8gN7fn5wfN1Kwfz8Hu2sJkXT+/nj361em\nfmUo/YNRkqj+tesL1eXWsRrtDuAIMB+YXk3XUSguKQLGjMGnv13KunSOAAC3sDBAk2kovW/mFh2N\n38jrbK/DX3qJ4GnTCPmPpsV0fNJkhzZclcD2vcpu8Ivi411qS1FzVJnBt8z0UyzPpZTyXillcyll\nRyllw0tUq1BUEY2feRqPDh0AMIQ7d3YTQhDx6qu0PbCftgf2E3D9aAC8LtNm9eZSewONnWQjqyzG\npk1p8dNGAE7cM5WC/ftdblNR/SgtHYWijhN4880EjB9P3tZteHbtcuETSuEWGWl73mb/v1Wa3MZg\nudsAyN74Ex5t21ZZ24rqQRl8haIeIITAu9fllT5PZzQS/n/PI0tMVZ7JTOj1NHn9dU4//DD5u3ZV\naduK6kEZfIXiEifgxhurrW3/a0eQt3UL2T9urLZrKKoOFYuvUChcwtC4Mab0dFuwl6Luogy+QqFw\nCUOwFjBZkqq0deo6yuArFAqXMIQEA1CUcOICNRW1jTL4CoXCJby6d0d4epK9bl1td0VxAZTBVygU\nLqH398ctLIz0r77CXFBQ291RnAdl8BUKhctYo20Tn3hSZcKqwyiDr1AoXCbqww8AyFq1itw//6zl\n3ijKQxl8hULhMt6l9H+KExLOU1NRmyiDr1AoXEYIQcyirwGcZtlS1A2UwVcoFFWCZ5cuGJs3p/iE\ncs+sqyiDr1AoqgxjZCRFJ9UMv66iDL5CoagyjDExFB07hrmwsLa7onCCMvgKhaLK8LqiF7KwUKln\n1lGUwVcoFFWGewstJaPy1KmbKIOvUCiqDLfGjQFIfOrpWu6JwhnK4CsUiipDGAwYmoSDlBQnJdV2\ndxTnoAy+QqGoUiLfehuA/L//JnP5csz5+bXcI4UVZfAVCkWV4t48FoD0b77l9KOzONx/gHLVrCO4\nbPCFEPcLIQ4KIfYJIV4tVf6YEOKI5dhQV6+jUCjqBzovLwxNwsnbuhUAc3Y2Jx94oJZ7pQAXc9oK\nIQYCo4BOUspCIUSopbwdMB5oDzQBfhRCtJJSmlztsEKhqPu4xzan5HSi7bUpNa0We6Ow4uoMfxrw\nspSyEEBKmWwpHwUsklIWSinjgCNATxevpVAo6gle3bsB4D2gP0F3303JmTPEjblR6eXXMq4a/FZA\nPyHEViHEr0KIyyzlEUBpQY2TlrIyCCGmCCG2CyG2nz171sXuKBSKukDQ1Km02v4XUR98gP+okQAU\n7NvHwS5dkVLWcu8aLhc0+EKIH4UQe508RqEtCQUCvYD/At8KIQQgnDTldJSllPOklD2klD1CQkJc\neCsKhaKuIIRA7+ODEAL3Fi1os9seeVty+nQt9qxhc0GDL6W8SkrZwcljOdrMfZnU2AaYgWBLeVSp\nZiIBNcoKRQNFGI0EjB8HwJHBV1GSklLLPWqYuLqk8z0wCEAI0QowAinACmC8EMJdCNEMaAlsc/Fa\nCoWiHhM+ezYYND+RrNWra7czDRRXDf4CIFYIsRdYBEy0zPb3Ad8C/wJrgXuVh45CoWi+dg0AxYkq\nCrc2cMktU0pZBEwo59gLwAuutK9QKC4tjJGReHTuRP4//9R2VxokKtJWoVDUKN6XXUb+3r1Is7m2\nu3JBpJQOXkUlaWkUHouzHzebkSUltdG1i0IZfIVCUaMYwsOhpARTWt0OxpJScqBtOw5270HynDkU\nHT/O0auHcGz4cFud07NmcbB7j1rsZeVQBl+hUNQohtBQAEqSk50eN+fnE3fTWOJuGEPR8eMAmDIz\nydm0qVr6k7liBcn/e7PMHYc5OxsAmZdH6gcfcnzSZMy5uVpZcTFFx4+TtWIlsrCQ4nriaqoMvkKh\nqFHcwsIAyhVUy/n5Zwr27KHg3385OnQYxUlJnJg6jRN33oUpJ6dK+1KSmsrpRx4ldd48cjdtwpSV\nRepHHyGLi8v8IJUk2qUiSpKTyd+71/Y67dPPqrRf1YVLm7YKhUJRWdxbt0a4u5O3dRt+Q4bYyvO2\nb6co4QSJjz/uUD/zu+9sm7wlyclkrliBzt2dgDFjXO5Lzq+/2Z6fuHsKfiOvI2vFSkw5Obg3bw5A\n088/I+2rr8hes9ZWN2ut/blHhw7kbt7scl9qAmXwFQpFjaJzd8dn4EAyf/iBsMdmIQwGihMTOT7h\nNlsdQ1gYzZYtJX7ceIelnMJDhzjz3PMAeHXvjjEm5qL7cfbtd0iZO9ehLGvFSgBSP/hQ66uXF+6t\nWhHx6quk9+iBR9u2HL/lVpJfex1jTAw6b2+8+/Uldd58zEVF6IxGAMxFRZx58UV8+vXDd/Dgi+5j\nVaOWdBQKRY3jN2wo5sxMstasIWPpUoflEYAWG3/EEBSER9u25G/fYSs/8/IrtudZ6zcAIEtKKD5z\n5oLXzN26jeT/vYkpI4OMpUsdjL01PuBc/K+/Hr2/P8LNjUa33opXt24ILy8AiuLjMefm4h7bHEwm\niuLibedlr1tHxqJvSH79jfP2qfBYHCXp6Rfse1WhDL5CoahxvPv2RR8QwOn/PkLiE0+SNPtZ2zFD\naCjCEpFrysy0n+TmRkmptIlFR49SnJhIyocfcmTAlefdODVlZ5MwcSKp8+ZxfOIkEp940uG4MSaG\niDlv4jtsGDFLl9jKQ2aU1fEPe/RRh9eeXbsAkPTss7Y+n/7vI1of4+KInzCBklIeSclz5pC1ejUZ\nS5ZwbPhwDl/Rm0N9+iJNJhLuuIP9bdqS9MKL5b4XV1BLOgqFosbR+/jQ5NVXODHlHgBMqam4t2uL\nzMun8bN24x88fToJ27aBXk/TTxY4LPtkb9hA5vLltte527YRMHq00+sVxdl95wsPHgSgyRuv49Gm\nDea8PAD8hg3Db9gwAGIWL8YYHYXez69MW4ZQR5FHY2QkXpdfTt7WrRSdPEXWDz84HM/fvoPTj86i\n8dNPUXw60bZcVBpTaipJzz1P7uY/AUj//HN0Pt6EzpihtbFrF27R0eT//TdnXniR2NWr0Hl4OH2v\n50PUJanSHj16yO3bt9d2NxQKRQ2R/u23JD39DABB06baDJwzpNnMgXbtAfC/4QYyly1zOO4/aiRN\nXnnFocycm4uUkrQFn5Aydy7BD9xPytvvAND67x3oLMszlUGaTORu2ULxiZN4dOyAZ/v25O/bR/yY\nGx3qBd9/HxnfLqbEyXKT3t/f8e7FgkenTgTddSenHtA+h2bfLSN90TdkfPONdl5gIKb0dGIWfY1H\np04kv/EGgePH4x4dvUNKecGAALWko1Aoao3AsWNpNGmS9qK4+Lx1hU5H5PtzaTRpEo1uK6vokr9n\nL4VHjpD+zbdIKTk7dy4Hu/fgcL/+pMydi7FZM3z69bfVvxhjDyD0enz69CFw/Dg822s/QMaoqDL1\ngqdMIWbR13j36VPmmNXYe/fu7VAe+e47+F59tRacBsRdf4PN2AM2t9T0rxdRFB9P2scLOHr1ECqK\nMvgKhaJWaTTxdoyxsfiNHHnBur4DBxI261E82rYl8r13HY4VHTvGsWuvI+mZZzg9c6ZtJi/z8wEI\nf+H/MEZrhtm9bdsqfQ/Oln6Emxtu4eGEPGi/azG2aE7grbdqfWjZgqgPPyDif/aNXbfQUIQQRH3w\ngfMLWX4UM5cv5/SsxyrdT7Wko1Ao6i05mzaR9vHH+I24lsQnnjhv3da7d6EzGslavx6v7t0xBAVV\naV8Kjx0jfuw4zDk5NHnjdfxHjLAdK0lNRZpM6Ly8KUlKJGvNWoLuvMN2l5G+6BsMoSH4DhpkOydu\nzI0U7NsHQNMvv+D4rU51KgFod/CAWtJRKBSXNj59+hC9YAEe7ds5PV56A9jqI+83ZEiVG3sA99hY\nQv/7X+15s2YOxwxBQbiFhqL38ca9RQtC7r/PYUkpcPw4B2MP0PTrr2i2Yjktf/8Nzy5dtKWesDCa\nfvWlQz3/cjaqnaFm+AqFot4jS0pIfPoZfAZeyan7NVdKryt6EfHqqxy2rNu3PbC/RvpiLixE5+5e\nvdfIz+dgVy1RfJv9/6LT6So0w1dumQqFot4jDAaavKil3xBz53Jy+nQCRo/GEBJCxFtvgaw5Kebq\nNvYAOk9PLUZAp0dLI14x1AxfoVBcckgpK2UI6ztCCLWGr1AoGiYNydhXBmXwFQqFooGgDL5CoVA0\nEJTBVygUigaCSwZfCNFFCLFFCLFTCLFdCNHTUi6EEG8LIY4IIXYLIbpVTXcVCoVCcbG4OsN/FXhW\nStkFeNryGuAaoKXlMQV438XrKBQKhcJFXDX4ErCKSPgDVkHqUcBnUmMLECCECHfxWgqFQqFwAVcD\nrx4E1gkhXkf78bBKv0UAJ0rVO2kpS+QchBBT0O4CiI6OdrE7CoVCoSiPCxp8IcSPQGMnh54ABgMP\nSSmXCiHGAh8DVwHOnGCdRnhJKecB8yzXyhZCHKxg3/2BsoLSla9T2bq1Va82r10d7yUYSKmFa6vx\nq9k2KzrOFW3zUvpsqvLarSvUipTyoh+WDlijdQWQZXn+IXBzqXoHgfAKtLe9EteeVxV1Klu3turV\nhz5W8r1UaKzr+nu5lMavmq5dK//T9eSzqbJrV/RzdnUN/zQwwPJ8EHDY8nwFcLvFW6cXkCmlLLOc\n4yIrq6hOZevWVr3avHZ1vJeKUtffy6U0ftXVZlVe+1L6bKrj2ufFJS0dIURf4C20paECYLqUcofQ\n4prfBYYBecBkKeUFRXKEENtlBfQgFPUfNdYNAzXONUNFP2eXNm2llH8A3Z2US+Dei2hyniv9UdQr\n1Fg3DNQ41wwV+pzrlFqmQqFQKKoPJa2gUCgUDQRl8GsYIUTOBY7/IoRQa571HDXODYP6Ns61YvAv\n9CEpLh2vkUxyAAAEGElEQVTUWDcM1DjXD9QMvxYQQlwphPih1Ot3hRCTarFLimpAjXPDoD6Nc60Z\nfCGEjxBioxDibyHEHiHEKEt5jBBivxBivhBinxBivRDCs7b6qXAdNdYNAzXOdZ/anOEXANdLKbsB\nA4E3hD0vWUvgPSlleyADGFNLfVRUDWqsGwZqnOs4roqnuYIAXhRC9AfMaOJqYZZjcVLKnZbnO4CY\nmu9etVKC44+tR211pIZoqGOtxlmNc52iNmf4twIhQHep6emfwf5BFZaqZ6J2f5iqg+NAOyGEuxDC\nH02E7lKmoY61Gmc1znWK2vzQ/YFkKWWxEGIg0LQW+1IjCCEMQKGU8oQQ4ltgN5r+0D+127Nqp0GN\ntRpnNc6127PyqXGDb/2QgC+BlUKI7cBO4EBN96UWaA8cBZBSPgI8cm4FKeWVNdynaqMBj7UaZzXO\nWMqvrOE+nZcal1YQQnQG5kspe9bohWsZIcRU4AHgQSnl+truT03QEMdajXPDoL6Oc40a/Pr6ISkq\njxrrhoEa5/qFEk9TKBSKBoKKtFUoFIoGQrUafCFElBDiZ0uU3T4hxAxLeSMhxAYhxGHL30BLuRBC\nvC2EOCKE2C2E6FaqrYmW+oeFEBOrs9+KylPFY71WCJFROlxdUTeoqnEWQnQRQvxpaWO3EGJcbb6v\nBkNFcypezAMIB7pZnvsCh4B2wKvALEv5LOAVy/PhwBq0AI5ewFZLeSPgmOVvoOV5YHX2XT1qZ6wt\nxwYD1wE/1Pb7Uo/qGWegFdDS8rwJkAgE1Pb7u9Qf1TrDl1ImSin/tjzPBvajRd+NAj61VPsUGG15\nPgr4TGpsAQKEEOHAUGCDlDJNSpkObEBLn6ioI1ThWCOl3Ahk12T/FRWjqsZZSnlISnnY0s5pIBkt\naEtRjdTYGr4QIgboCmwFwqQlqbnlb6ilWgRwotRpJy1l5ZUr6iAujrWinlBV4yyE6AkYsfi0K6qP\nGjH4QggfYCma61bW+ao6KZPnKVfUMapgrBX1gKoaZ8td3efAZCmluWp7qTiXajf4Qgg3tC/Gl1LK\nZZbiM9bbd8vfZEv5SSCq1OmRwOnzlCvqEFU01oo6TlWNsxDCD1gFPGlZ7lFUM9XtpSOAj4H9Usr/\nlTq0ArB62kwElpcqv92ys98LyLTcHq4DhgghAi27/0MsZYo6QhWOtaIOU1XjLIQwAt+hre8vrqHu\nK6pzRxjoi3b7thtNW2Mn2q59ELARTWhoI9DIUl8A76Gt5e0BepRq6w7giOUxubZ3u9WjWsf6d+As\nkI82Qxxa2+9PPap2nIEJQHGpNnYCXWr7/V3qDxVpq1AoFA0EFWmrUCgUDQRl8BUKhaKBoAy+QqFQ\nNBCUwVcoFIoGgjL4CoVC0UBQBl+hUCgaCMrgKxQKRQPh/wGKj6DhpuVi7AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9bab80fa58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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jZduT6fD8ZNa9cGmhxtLkpH0iSoVAz5bZ85Z8cns85zWvWYylsbWctwd04KGL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\n72x6B4D29dsTGR7p6aa9qfdNXts+/PXD5LhyuP3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SBmAQ8ICIuIBCYJKqHgxQ+saYaiKq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9bab80fdd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df.plot? for more help\n",
    "df.plot()\n",
    "df.plot(title='DataFrame cumsum', figsize=(4, 12), subplots=True, sharex=True, sharey=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x8c14ab0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ly/l/w/8fMVn103o5VzIzZbrlf//bpG/TKDQNli6FsDCTawgaXzy2dy9s2SJXCbt2Qe/e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\nREQEBQMREUHBQEREUDAQERHg/wF2TspMnZGWPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8acfbb0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['I'] = np.arange(len(df))\n",
    "df.plot(x='I', y=['A', 'C'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.251322</td>\n",
       "      <td>0.710449</td>\n",
       "      <td>0.677939</td>\n",
       "      <td>0.187400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.082089</td>\n",
       "      <td>0.793091</td>\n",
       "      <td>0.021801</td>\n",
       "      <td>0.287124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.911240</td>\n",
       "      <td>0.802222</td>\n",
       "      <td>0.429064</td>\n",
       "      <td>0.956067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.477370</td>\n",
       "      <td>0.234396</td>\n",
       "      <td>0.303595</td>\n",
       "      <td>0.945137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.471124</td>\n",
       "      <td>0.205507</td>\n",
       "      <td>0.499160</td>\n",
       "      <td>0.887754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.389382</td>\n",
       "      <td>0.062298</td>\n",
       "      <td>0.110157</td>\n",
       "      <td>0.705081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.068719</td>\n",
       "      <td>0.325747</td>\n",
       "      <td>0.951594</td>\n",
       "      <td>0.501131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.365177</td>\n",
       "      <td>0.950995</td>\n",
       "      <td>0.898784</td>\n",
       "      <td>0.822838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.022807</td>\n",
       "      <td>0.721682</td>\n",
       "      <td>0.651013</td>\n",
       "      <td>0.212020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.497862</td>\n",
       "      <td>0.596736</td>\n",
       "      <td>0.486710</td>\n",
       "      <td>0.672207</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D\n",
       "0  0.251322  0.710449  0.677939  0.187400\n",
       "1  0.082089  0.793091  0.021801  0.287124\n",
       "2  0.911240  0.802222  0.429064  0.956067\n",
       "3  0.477370  0.234396  0.303595  0.945137\n",
       "4  0.471124  0.205507  0.499160  0.887754\n",
       "5  0.389382  0.062298  0.110157  0.705081\n",
       "6  0.068719  0.325747  0.951594  0.501131\n",
       "7  0.365177  0.950995  0.898784  0.822838\n",
       "8  0.022807  0.721682  0.651013  0.212020\n",
       "9  0.497862  0.596736  0.486710  0.672207"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.rand(10, 4), columns=['A', 'B', 'C', 'D'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x8cb5030>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+PycJ8SPA1UmuBO4BdgN7hmpuA/4A+Kck1wHfqKozwweqqlauFElqwtgQr6pzSfYBh+lN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\nl6SGGeKS1DBDXJIa9n/bNg+5aPbR0gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8cbf130>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.ix[1].plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x8cec490>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+PycJ8SPA1UmuBO4BdgN7hmpuA/4A+Kck1wHfqKozwweqqlauFElqwtgQr6pzSfYBh+lN\nvxysqqNJ9vZ214Gq+rckv5Tki8C3gZetbduSJIBU1ax7kCRdJG9sSlLDDPERktyQ5C2z7kMbW5Kr\nk1w/Yvv1SZ44i540fwzxviRPT/JXSb4C/DmwNOOW1o0kl6edjz/MkzcB3xyx/Zv9fbpISR6f5PGz\n7mMaNnSIJ7kmyc1JloA3A/9F7z7Bs6vqzTNur0lJrkvSTfLu/l+MXwC+AJxJsjDr/hqzpao+P7yx\nv+2qh76dtqVnMcl9wJ3AsSRfTfJns+5tNTZ0iNMbbT8HeH5V3dAP7nMz7ql1twB/AbwD+CDw8qra\nCjwLeMMsG2vQY1fY9/CHrIv149XA9cAzq+qyqnoc8LPA9UlePdvWLt5GD/EX0vvs+4eSvD3JTtbm\n2wQbyeaqOlxV/wzcW1UfB6gqp6cu3CeT/O7wxiQvBz41g35a9xJgT1V9+YENVXUX8FvAS2fW1SpN\n8mWfdauqbgVuTfIIev+I16uAH03yNuA9VXV4pg226fsDy/cP7fPzrBfmVcB7kvwm/x/aPwNcCvzK\nzLpq18Oq6r7hjVX11SQPm0VD0+DnxIckeRzw68CLqmrnrPtpTZJz9L7wFXq/8n/ngV3AD1dVs/+z\nzEqSZwM/2V/9j6r64Cz7aVWST1fVMy5037wzxCVtCAMDjAftouEBhiEuSQ3b6Dc2JalphrgkNcwQ\nl6SGGeKS1DBDXJIa9n/bNg+5aPbR0gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8edea50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.ix[1].plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x8f2bf70>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CM7MccxE3M8sxF3GzhPzt6pZF7hM3S8jfrm5Z5CNxM7MccxE3M8sxF3Ezsxxzn3gN3b29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\nNzPLMRdxM7MccxE3M8sxF3Ezsxz7/zEr7cJj1Y0/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8f47330>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.bar(stacked=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x9676070>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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c0iDhvU1YYZmOFPcdb0elOH4T2X89QwXdgz3VFZZmNtfMvm9mvzCzJ8zs6lYuBABITsiw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\noal1awniMQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x96764b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.barh(stacked=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 直方图\n",
    "\n",
    "直方图是一种对值频率进行离散化的柱状图。数据点被分到离散的，间隔均匀的区间中，绘制各个区间中数据点的数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({'a': np.random.randn(1000) + 1, 'b': np.random.randn(1000),\n",
    "                   'c': np.random.randn(1000) - 1}, columns=['a', 'b', 'c'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x96c25b0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tBoMkqcVgkDSDTiDJxG8LC9u6fqEzyQv1aFleqGce2plmW+vzNW2k9xIv1CNJWpOurvms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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8874410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['a'].plot.hist(bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x087FF030>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x0878F5B0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x086AFFB0>], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xbEQ8X9MPcCXVpqDNwP41uw2ZpK7meIW/5s+fX3gZyvLytfC18LUo/7VoJO/RRHtVmoAk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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x87ed830>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.hist(subplots=True, sharex=True, sharey=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x85ed350>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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K/A3wZvL6m4j42um2k/QDSd2Sfl/WtlTSTknPJ69ryz5bLGm7pC2S5gz9zzEzszNR6TAR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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x85e5870>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.hist(alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x9712bb0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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I0u8XEtkASL0PsExuizauGTR5u2hJvS06TQZvA34aEUcBJI0AJ0bEUxHxpcKiMzOzUnRa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\nMDMznAzMzAwnAzMzw8nAzMyA/w/cDkT3Szb5CgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x98c3d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.hist(stacked=True, bins=20, grid=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 密度图\n",
    "\n",
    "正态分布（高斯分布）就是一种自然界中广泛存在密度图。比如我们的身高，我们的财富，我们的智商都符合高斯分布。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x9be2910>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Sv3P3Ae7+E3d/DcDMdgBw9yMTSydSJJkMVOJ1qDR4LUnLt0j8qIn7nihmEJEkZTKVNWjd\nSIPXkrQWL19qZvsSrkm9o5kdQbjeA8CuhK4nkbK3cWMY4K3EZbUHDoTf/CZ2CqlkrV3jejRhsLoX\nkHvZ0E3ApQllEimqxx8PBaLSxiNg2zOcOmgWkySgxSLh7n8E/mhmX3D3O0uUSaSoHnmkMscjIFyh\nbs89Yfly6Ns3dhqpRK11N/2zu/8J6GNml2z/uLtf1UQzkbKSycDPfx47RXIaB69VJCQJrR2gNi5g\nsAvQrYkvkbL29tvhA7QSxyMaafBaktRad9Nvs9+/39YXMLMxwDWEgnSTu1+53eNfBiZlNzcB/+ru\nf8unrUhrKnk8otHAgeFoSSQJ+U6m+6mZ7Wpmnc3sITNba2b/nEe7DsB1hAHwgcDZZtZ/u92WASe4\n+2DCqbZTCmgr0qJKnR+RS0cSkqR8z4f4rLu/DXyOsHbTQcB38mg3HFjq7ivcvR6YCozN3cHd57r7\nxuzmXMIpt3m1FWlNJgOjRsVOkawBA2DxYq3hJMnIt0g0dkudBtyR86Hemp7AypztVXxcBJryNeC+\nNrYV2UbjeMTRR8dOkqxu3aB793CGk0ixtTZPotH/mtli4H3gm2a2F/BBMYOY2WeA84Hj2tK+trb2\no9s1NTXUVHofg7Rq9uzKXK+pKY1dTjrDSZqTyWTItGHwyjzPK6mb2Z7ARnffamY7Abu6++uttBkB\n1Lr7mOz2ZMCbGLw+HLgTGOPuLxfSNvuY5/tzSPWYNAl23BFy/n6oWN/+NvToAZMnx04iaWFmuLu1\ntl8hczT7A18ys3OBfwI+m0ebecBBZnaAmXUBxgF3bxe0N6FAnNNYIPJtK9KS2bPh+ONjpygNDV5L\nUvLqbjKz/wH6AQuBrdm7Hbi5pXbZo46JwEw+Po21zszGh4d9CvD/gT2BX5uZAfXuPry5toX/iFKN\nNm+GBQsqfzyi0cCBcO21sVNIJcqru8nM6oAB5dqno+4m2d4TT8CECfDMM7GTlMamTbDvvmGwvmPH\n2GkkDYrd3fQcsG/7IomUzuzZMHJk7BSl061bGJPQGU5SbPme3dQDeMHMngI2N97p7qcnkkqknebM\ngS9+MXaK0ho0KFyitV+/2EmkkuRbJGqTDCFSTO7hSOKaa2InKa1Bg8Lg9VhNOZUiyqu7yd0fIcy0\n7py9PQ+okt5eSZtly6BzZ9h//9hJSqvxSEKkmPJdu+nrwDTgt9m7egIzkgol0h6N4xHW6pBcZVGR\nkCTkO3A9ARgJvA3g7kuBvZMKJdIec+bAscfGTlF6/fvD0qVQXx87iVSSfIvEZnf/sHHDzDoR5kmI\nlJ1qO7Op0Y47Qu/eoVCIFEu+ReIRM7sU2NHMTgbuAO5JLpZI27z9dhiTGDw4dpI4Bg2CZ5+NnUIq\nSb5FYjKwFngWGA/cC3w3qVAibfXMM6FAdO4cO0kcGpeQYsvrFFh3bzCzGcAMd1+bcCaRNps3L6z8\nWq0GDYJbb42dQipJi0cSFtSa2ZvAi8CL2avSfa808UQKM38+HHlk7BTx6EhCiq217qaLCWc1HeXu\ne7r7nsDRwEgzuzjxdCIFqvYjiYMOglWr4L33YieRStFakTgHONvdX2m8w92XAf8MnJtkMJFCvfkm\nvPUWfPrTsZPE07lz+PnrtF6yFElrRaKzu7+5/Z3ZcYkqHRqUcvX00zB0KHQo5CopFUhdTlJMrf13\n+rCNj4mUXLV3NTVSkZBiaq1IDDazt5v42gQcVoqAIvlSkQhUJKSYWiwS7t7R3Xdt4qubu6u7ScpK\ntZ/Z1EhFQoqpyntvpVKsWRMuWdqnT+wk8R1wAKxfDxs2xE4ilUBFQipCY1dTta382pQOHcI1r3U0\nIcWQeJEwszFmttjMlpjZpCYeP8TM5pjZB2Z2yXaPLTezRWa2IHtVPJEmqatpW4MHw6JFsVNIJUi0\nSJhZB+A6YDQwEDjbzPpvt9tbwEXAz5p4igagxt2PcPfhSWaVdNOg9baOOAIWLIidQipB0kcSw4Gl\n7r7C3euBqcA2F1d09zfd/WlgSxPtrQQZJeXcQ5HQkcTHhgyBhQtjp5BKkPQHcE9gZc72qux9+XLg\nATObl706nsgnLF8OXbvCfvvFTlI+Dj8cXnhBFyCS9strFdiIRrr7a2a2F6FY1Ln7403tWFtb+9Ht\nmpoaampqSpNQolNX0yftvHO4AFFdXSgYIplMhkwmU3C7pIvEaqB3znav7H15cffXst/Xmtl0QvdV\nq0VCqou6mpp2xBGhy0lFQuCTfzx///vfz6td0t1N84CDzOwAM+sCjAPubmH/j05gNLOdzGyX7O2d\ngc8COqlPPmH+fB1JNEWD11IMiR5JuPtWM5sIzCQUpJvcvc7MxoeHfYqZ7QPMB7oBDWb2LWAAsBcw\n3cw8m/MWd5+ZZF5Jn4aGsLCfjiQ+acgQuO++2Ckk7czdY2doNzPzSvg5pHB1dXDaaeG61rKttWvD\nsuHr1mmSoXySmeHurb4zdHqppJq6mpq3115hAHv58thJJM1UJCTVdGZTy4YM0biEtI+KhKSaluNo\n2ZFHht+RSFupSEhq1deH9YmGDo2dpHwNHw5PPhk7haSZioSk1vPPhwlju+4aO0n5Gj48HEls3Ro7\niaSVioSklsYjWtejRxjAfvHF2EkkrVQkJLVUJPKjLidpDxUJSa1588IHoLTs6KNVJKTtVCQkld57\nL3ShDB4cO0n5U5GQ9lCRkFRauBAGDAhLhEvLhgwJBfW992InkTRSkZBUeuopdTXlq2tXGDRI8yWk\nbVQkJJU0aF2Y44+HRx+NnULSSEVCUklHEoUZNQoeeSR2CkkjrQIrqbNuHfTpA+vXQ8eOsdOkw/r1\nYeLhunXQuXPsNFIOtAqsVKz588NSHCoQ+dtjD+jXL1x7Q6QQKhKSOhqPaBt1OUlbqEhI6mg8om1U\nJKQtNCYhqeIO++0HTzwRxiUkf2++Gbqc3noLOiV64WJJA41JSEVavTqsaHrAAbGTpE+PHtC3r2Zf\nS2ESLxJmNsbMFpvZEjOb1MTjh5jZHDP7wMwuKaStVJ8nngjLTOiazW1zyilw332xU0iaJFokzKwD\ncB0wGhgInG1m/bfb7S3gIuBnbWgrVWbOHBg5MnaK9DrlFLj33tgpJE2SPpIYDix19xXuXg9MBcbm\n7uDub7r708CWQttK9Zk9W0WiPY45Bl55BV5/PXYSSYuki0RPYGXO9qrsfUm3lQr03nvhanS6pnXb\ndeoE//APcP/9sZNIWlTMOQ61tbUf3a6pqaGmpiZaFknGvHlw2GGw446xk6Tb5z4HM2bAeefFTiKl\nlMlkyGQyBbdL9BRYMxsB1Lr7mOz2ZMDd/com9r0c2OTuV7WhrU6BrQI//nE4jfOqq2InSbcNG8LZ\nYatWQbdusdNILOVyCuw84CAzO8DMugDjgLtb2D83cKFtpcJp0Lo4dt89rAp7zz2xk0gaJFok3H0r\nMBGYCTwPTHX3OjMbb2YXApjZPma2ErgYuMzMXjWzXZprm2ReKV8NDaFIHHts7CSV4ayz4PbbY6eQ\nNNCMa0mFujo47TRYtix2ksqwYUNYFXbFirD4n1SfculuEimKRx+F446LnaJy7L57mDNxyy2xk0i5\nU5GQVHj4YfjMZ2KnqCzjx8OUKWE9LJHmqEhI2XOHTEZFothqauD997WWk7RMRULKXl1dmBuhVV+L\nq0MHuPBCuP762EmknFXMZDqpXOpqSs7Xvx6WD3/lFTjwwNhppBzpSELKnopEcnbfPYxN/Oxnre8r\n1UmnwEpZa2iAvfeGhQuhV6/YaSrT3/8O/fvD3/6m33E10SmwUhEWLQrn8evDKzl77w3f/CZcemns\nJFKOVCSkrN1/P4wZEztF5Zs8GR58MCyiKJJLRULK2v33h0lfkqxu3eCHP4SLLw5dfCKNVCSkbG3c\nCM88E87nl+Sddx7U18ONN8ZOIuVERULK1kMPhQX9dtopdpLq0LFjKBCXXQarV8dOI+VCRULKlrqa\nSu+ww8Ig9oQJWq5DAhUJKUvuGrSO5bLL4MUXYdq02EmkHKhISFlasAB22AEOOSR2kuqzww6h2+lb\n34L162OnkdhUJKQsTZ8On/88WKtTfSQJI0fC6aeHowqpbppxLWVp0CD43e/gmGNiJ6le69fDoYfC\n3XfD8OGx00ixaca1pNbSpbBuHRx9dOwk1W2PPeCnPw0D2Vu3xk4jsSReJMxsjJktNrMlZjapmX1+\nZWZLzWyhmR2Rc/9yM1tkZgvM7Kmks0p5mD4dxo4NS1lLXOecEybaTZkSO4nEkuh/QzPrAFwHjAYG\nAmebWf/t9jkF6OfuBwPjgd/kPNwA1Lj7Ee6uA94q8Ze/wBlnxE4hEMaErroKfvAD2LQpdhqJIem/\n1YYDS919hbvXA1OBsdvtMxa4GcDdnwR2M7N9so9ZCTJKGXn5ZVi2DE48MXYSaTR0aPj3+MUvYieR\nGJL+AO4JrMzZXpW9r6V9Vufs48ADZjbPzL6eWEopG3/+M5x1FnTuHDuJ5PrRj+Daa+H112MnkVIr\n97/SR7r7UOBUYIKZHRc7kCTHHW65Bb7yldhJZHsHHgjnngv/9V+xk0ipJX350tVA75ztXtn7tt9n\n/6b2cffXst/Xmtl0QvfV4029UG1t7Ue3a2pqqNGqcKmzcCFs3gwjRsROIk2ZPDmcEvuf/wn77Rc7\njRQqk8mQyWQKbpfoPAkz6wi8CJwEvAY8BZzt7nU5+5wKTHD308xsBHCNu48ws52ADu7+jpntDMwE\nvu/uM5t4Hc2TqADf/naY7au/VsvXxReH71dfHTeHtF++8yQSn0xnZmOAXxK6tm5y9yvMbDzg7j4l\nu891wBjgXeB8d3/GzA4EphPGJToBt7j7Fc28hopEym3eDL17w+OPw8EHx04jzVmzJkx0rKuDffZp\nfX8pX2VTJEpBRSL9br8dbrgBZs2KnURaM3FiWL79pz+NnUTaQ0VCUuXkk+GCC+Dss2MnkdasXAmD\nB4eVYvfaK3YaaSsVCUmNZcvCEhwrV0LXrrHTSD6+8Q3Yc0/48Y9jJ5G2UpGQ1PjOd8J1lTVZKz1W\nrAiT7JYsge7dY6eRtlCRkFR4++1wDv7TT0OfPrHTSCHGj4cePXQ2WlqpSEgqXH01PPkkTJ0aO4kU\nSkcT6aYiIWVvyxbo1y9cJvOoo2Knkba48MIweK2jifRRkZCyd/PN8PvfQxsmgUqZWL4chg3T0UQa\nqUhIWfvwQ+jfH/77v+GEE2Knkfa48ELYe++wCKCkh4qElLUbbggXF/rrX2MnkfZqPJp47jn41Kdi\np5F8qUhI2dqwAQYMCNdOPvLI2GmkGP7jP+Ctt+Cmm2InkXypSEjZmjgxDFrfcEPsJFIsGzfCIYfA\nvfeGM56k/KlISFl68slw/eoXXggzdqVyTJkSxpgeeww6doydRlqTb5Eo94sOSQXZuDGszXT99SoQ\nlehrXwtXFLzmmthJpJh0JCEl0dAQLku6997w61/HTiNJaVyH67HHwtlrUr50JCFlwx3+/d/h73+H\nq66KnUaS1LdvOBX2rLPgnXdip5Fi0JGEJGrrVrjkEnjkkTBpbvfdYyeSpLmHrqcNG+COO6CD/hQt\nSxq4lujeeAPOPz9cde7OO1UgqsnmzTB6NBx0UBjQVqEoP+pukmjq6+F3vwsXphk8GO67TwWi2uyw\nA/zv/4blOs49F95/P3YiaSsVCSmad9+FG28ME+WmTg0fEj/5CXTpEjuZxLDLLuEPhC1b4Pjjw3Wx\nJX0SLxJmNsbMFpvZEjOb1Mw+vzKzpWa20MyGFNJW4nKHBQvgoougd+8wi/q3v4WHHtJsaoGdd4Y/\n/zl0O55wAkyaFLohJT0SLRJm1gG4DhgNDATONrP+2+1zCtDP3Q8GxgM35Nu2EmRSuASqOyxcCJdd\nBr16Zfinf4I99gj33X03nHhi7IT5S+PvP1ca8pvBhAnh/fHOO3DooXDOOXDPPTBzZiZ2vHZJw++/\nvZI+khgOLHX3Fe5eD0wFxm63z1jgZgB3fxLYzcz2ybNt6qXhTeYOq1bBrbfCeedBr15w5pmhG+G0\n0zK89BL84Aew//6xkxYuDb//lqQpf8+eYSLl4sUwYgT8/Ofh/TNyZLiE7c03w/z56Tp1Nk2//7bq\nlPDz9wRi/mlyAAAFD0lEQVRW5myvInz4t7ZPzzzbShHV18PatfDKK2FS1Esvha6kefNCQRg5Ej77\nWfjud8PFgsygtjZ8F8nX3nuHI4sJE+DSS+Gkk2DuXLj//jCPZsmScCGjvn3DJW0PPDB879Mn/CHS\nvTt066b3XakkXSTaoqT/9M8/H/pJIfzF3NL39u7T1H3Ll8OsWcm+Rkv7bNkSzmdfvz6ctti9e/hP\n2bdvKARf/Spce20Yb9B/Sim2Ll1CkTjppI/v27o1/L9Yvjz8wbJ8OcycGW6vWgXr1sEHH4Quzj32\ngK5dw/M0fnXuvO0pt9u/b3O387ndkhdfDNdnj6VDB7jrrmRfI9F5EmY2Aqh19zHZ7cmAu/uVOfvc\nADzs7rdltxcDo4ADW2ub8xyaJCEiUqB85kkkfSQxDzjIzA4AXgPGAWdvt8/dwATgtmxR2eDub5jZ\nm3m0BfL7QUVEpHCJFgl332pmE4GZhEHym9y9zszGh4d9irvfa2anmtlLwLvA+S21TTKviIhsqyKW\n5RARkWRUzIxrM7vIzOrM7FkzuyJ2nrYws/9nZg1mlqqrLZjZT7O/+4VmdqeZ7Ro7U2vSPFHTzHqZ\n2Swzez77fv+32Jnawsw6mNkzZnZ37CyFMrPdzOyO7Pv+eTM7OnamQpjZxWb2nJn9zcxuMbNm10Wo\niCJhZjXAPwKHufthwM/jJiqcmfUCTgZWxM7SBjOBge4+BFgK/GfkPC2qgImaW4BL3H0gcAwwIWX5\nG30LeCF2iDb6JXCvux8KDAZS0xVuZvsBFwFD3f1wwrDDuOb2r4giAXwTuMLdtwC4+5uR87TF1cB3\nYodoC3d/0N0bsptzgV4x8+Qh1RM13f11d1+Yvf0O4QOqZ9xUhcn+UXQqcGPsLIXKHikf7+5/AHD3\nLe7+duRYheoI7GxmnYCdgDXN7VgpReLTwAlmNtfMHjazVK0aZGanAyvd/dnYWYrgAuC+2CFa0dwE\nztQxsz7AEODJuEkK1vhHURoHRQ8E3jSzP2S7y6aY2Y6xQ+XL3dcAvwBeBVYTzih9sLn9y3EyXZPM\n7AFgn9y7CG+w7xJ+jj3cfYSZHQXcDvQtfcrmtZL/UkJXU+5jZaWF/Je5+z3ZfS4D6t391ggRq46Z\n7QJMA76VPaJIBTM7DXjD3Rdmu4rL7v3eik7AUGCCu883s2uAycDlcWPlx8x2Jxw5HwBsBKaZ2Zeb\n+3+bmiLh7ic395iZfQP4S3a/ednB3+7u/lbJAraiufxmNgjoAywyMyN01TxtZsPd/e8ljNiiln7/\nAGZ2HqH7IA3L+60Geuds98relxrZboJpwP+4e8JzbotuJHC6mZ0K7Ah0M7Ob3f3cyLnytYpw5D8/\nuz0NSNPJD/8ALHP3dQBm9hfgWKDJIlEp3U0zyH44mdmngc7lVCBa4u7Pufu+7t7X3Q8kvAGPKKcC\n0RozG0PoOjjd3TfHzpOHjyZ5Zs/qGEeY1JkmvwdecPdfxg5SKHe/1N17u3tfwu9+VooKBO7+BrAy\n+1kDcBLpGoB/FRhhZl2zf5ieRAsD76k5kmjFH4Dfm9mzwGYgNW+4JjjpO/y+FugCPBDec8x193+N\nG6l5aZ+oaWYjga8Az5rZAsJ75lJ3vz9usqryb8AtZtYZWEZ2EnAauPtTZjYNWADUZ79PaW5/TaYT\nEZFmVUp3k4iIJEBFQkREmqUiISIizVKREBGRZqlIiIhIs1QkRESkWSoSIiLSLBUJERFp1v8Bn2cq\nTYAHgd8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9bed490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['a'].plot.kde()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xa161db0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JvA4d4ORJOHECmjZ1ElLVEVU1NzXyfW0MNCnnplT1cNzUVFRSxI6jO+jRqkfE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\n/wNufTv1wr+joAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xa17e230>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.kde()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    0.947151\n",
       "b   -0.026500\n",
       "c   -1.039657\n",
       "dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1.014101\n",
       "b    1.028685\n",
       "c    1.030285\n",
       "dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.std()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 带密度估计的规格化直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    400.000000\n",
       "mean       5.172248\n",
       "std        5.397582\n",
       "min       -3.644105\n",
       "25%        0.061406\n",
       "50%        3.691510\n",
       "75%       10.250011\n",
       "max       16.031112\n",
       "dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n1 = np.random.normal(0, 1, size=200) # N(0, 1)\n",
    "n2 = np.random.normal(10, 2, size=200) # N(10, 4)\n",
    "s = pd.Series(np.concatenate([n1, n2]))\n",
    "s.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xa17e2f0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tXw6zZ3sfrE1RYSEcfTTcfrv/8ue//rV3a+7rr0NOTqDhRV7r1jya/03O/OAx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\nYYiIiC//D/v/1kGiw73GAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xa23f970>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot.hist(bins=100, alpha=0.5, normed=True)\n",
    "s.plot.kde(style='r-')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 散布图\n",
    "\n",
    "散布图是把所有的点画在同一个坐标轴上的图像。是观察两个一维数据之间关系的有效的手段。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fHB5JSJI2WarW/Lu8ub84OQX0quqZJP8CeLCqfqrRbgfwZ8Cnquq/XuI9u/nHSNIWVlVp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9c10f70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])\n",
    "df.plot.scatter(x='a', y='b');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>400.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.974366</td>\n",
       "      <td>5.035267</td>\n",
       "      <td>5.011259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.158428</td>\n",
       "      <td>5.492017</td>\n",
       "      <td>6.572784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-3.149143</td>\n",
       "      <td>-5.022496</td>\n",
       "      <td>-13.671181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.079920</td>\n",
       "      <td>-0.130532</td>\n",
       "      <td>-0.128582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.800326</td>\n",
       "      <td>5.587717</td>\n",
       "      <td>4.901682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.923731</td>\n",
       "      <td>10.139781</td>\n",
       "      <td>10.002299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.688234</td>\n",
       "      <td>16.233516</td>\n",
       "      <td>19.855104</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                a           b           c\n",
       "count  400.000000  400.000000  400.000000\n",
       "mean     2.974366    5.035267    5.011259\n",
       "std      3.158428    5.492017    6.572784\n",
       "min     -3.149143   -5.022496  -13.671181\n",
       "25%      0.079920   -0.130532   -0.128582\n",
       "50%      2.800326    5.587717    4.901682\n",
       "75%      5.923731   10.139781   10.002299\n",
       "max      8.688234   16.233516   19.855104"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({'a': np.concatenate([np.random.normal(0, 1, 200), np.random.normal(6, 1, 200)]),\n",
    "                  'b': np.concatenate([np.random.normal(10, 2, 200), np.random.normal(0, 2, 200)]),\n",
    "                  'c': np.concatenate([np.random.normal(10, 4, 200), np.random.normal(0, 4, 200)])})\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x131d6930>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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I2U1x8IrFXJWgmWYA+fwW7em5SPv6LtPp6Wnt67u8yjbLbud9dbC93hlBtwe4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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x13281590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='a', y='b')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 饼图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    0.505096\n",
       "b    0.295620\n",
       "c    2.855217\n",
       "d    2.716670\n",
       "Name: series, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series(3 * np.random.rand(4), index=['a', 'b', 'c', 'd'], name='series')\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1338bbd0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0Jph4tqp/p+toxWKFvQLdRF68CPb5LwKxKtWYFcoAB4L3ZgyS55RBWTcB4/D4gDD+7h7+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\nhBW2McYExP8B40R28o9Dd0AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x134e9d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot.pie(figsize=(6,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1352bf30>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ydE+R9tIfKse6KXn3tfIljsUF7efAlyt4ziHAviKyjqrOwPWHK/AUrqOqqU64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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1324ad10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s.plot.pie(labels=['AA', 'BB', 'CC', 'DD'], colors=['r', 'g', 'b', 'c'],\n",
    "           autopct='%.2f', fontsize=20, figsize=(6, 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>1.115819</td>\n",
       "      <td>2.348513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>2.681690</td>\n",
       "      <td>0.816831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.855954</td>\n",
       "      <td>0.380417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>2.235465</td>\n",
       "      <td>1.958050</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "a  1.115819  2.348513\n",
       "b  2.681690  0.816831\n",
       "c  0.855954  0.380417\n",
       "d  2.235465  1.958050"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(3 * np.random.rand(4, 2), index=['a', 'b', 'c', 'd'], columns=['x', 'y'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x135578D0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x138097F0>], dtype=object)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UmloAPIQh10fgQdtpqkAmRIXOTIjI6cA/jTGLivDwmwCjjDETROQ+4BTgj6v8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\nCCAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1370b7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.pie(subplots=True, figsize=(9, 4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 高级绘图\n",
    "\n",
    "高级绘图函数在 pandas.tools.plotting 包里。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qGsflqqLrZ6jXS7TbVhKJMIuLM9jtBiIRnUDAgsfjJxQKMDYGqZSbVGqARqNC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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1328b250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import scatter_matrix\n",
    "df = pd.DataFrame(np.random.randn(1000, 4), columns=['a', 'b', 'c', 'd'])\n",
    "scatter_matrix(df, alpha=0.2, figsize=(6, 6), diagonal='kde');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "s = pd.Series(0.1 * np.random.rand(1000) + 0.9 * np.sin(np.linspace(-99 * np.pi, 99 * np.pi, num=1000)))\n",
    "y = np.linspace(-99 * np.pi, 99 * np.pi, num=1000)\n",
    "s.plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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B3r0niEQilJeXEw4vYOvWX6U51yuITIfnDqurq0mIY6Sr8O6rJLoHa5DmV+udx6MQ8ccG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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1429c210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import lag_plot\n",
    "\n",
    "s = pd.Series(0.1 * np.random.rand(1000) + 0.9 * np.sin(np.linspace(-99 * np.pi, 99 * np.pi, num=1000)))\n",
    "lag_plot(s);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QXT76qCQ6//ijLEE/80wZ17gxc4MGklT9wAPMO3bI+GnTJGYX/nw+GhUAlQG8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\nFAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x13e40870>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import autocorrelation_plot\n",
    "\n",
    "s = pd.Series(0.7 * np.random.rand(1000) + 0.3 * np.sin(np.linspace(-9 * np.pi, 9 * np.pi, num=1000)))\n",
    "autocorrelation_plot(s);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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